JP2010049363A - Log information analysis visualization device, log information analysis visualization method, log information analysis program, and storage medium stored with the program - Google Patents

Abstract

Log information is analyzed by inputting a simple natural sentence, and a target analysis result is visually displayed.
A log information analysis visual apparatus that analyzes log information accumulated by an operation of an image processing apparatus and displays an analysis result, and analyzes for analyzing at least the log information from an input natural sentence Pattern sentence specifying means for specifying a pattern sentence configured using items and expression formats, and log information collecting means for collecting the log information based on an analysis item included in the pattern sentence specified by the pattern sentence specifying means And the screen control means for generating a screen showing the analysis result by the expression format included in the pattern sentence specified by the log information collecting means.
[Selection] Figure 2

Description

  The present invention relates to a log information analysis visual device, a log information analysis visual method, a log information analysis program, a log information analysis program, and a storage medium storing the program, which analyze log information accumulated by operation of an image processing apparatus and display the analysis result.

  Conventionally, in various log systems, log information such as computer processing history and user operation history is accumulated and stored. Also in an image processing apparatus such as a multi-function copying machine (hereinafter referred to as “MFP”) having a plurality of functions such as copying, scanning, and faxing, various types of log information associated with image processing operations are recorded. Has been.

  The contents of these stored log information are diverse. By analyzing and analyzing the log information, for example, you can investigate the usage status of MFP, conduct audits for security purposes, conduct document management surveys, etc. It can be considered to be used for various purposes.

Conventionally, for example, since a computer administrator or the like collects only necessary information from log information that has a huge amount of information, log information is displayed on the screen by keyword search, and unnecessary log information is displayed from the displayed log information. An apparatus that edits the contents of log information by deleting information or the like is known (see, for example, Patent Document 1).
JP 2005-165456 A

  However, according to the technique described in Patent Document 1, the log information including the keyword is simply displayed on the screen as a result of keyword search. For example, by analyzing the log information, Information such as how many violation documents were output each month cannot be visualized with a graph or the like and used for the intended investigation.

  In addition, in order to obtain the target graph from various log information, it is necessary to input complicated search conditions, and there are many systems that require custom-made such as simple programming on the user side. The work which required was forced.

  The present invention has been made in view of the above points, a log information analysis visual device that can analyze log information by inputting a simple natural sentence and visually display a target analysis result, It is an object to provide a log information analysis visual method, a log information analysis program, and a storage medium storing the program.

  In order to solve the above problems, the present invention is a log information analysis visual device that analyzes log information accumulated by operation of an image processing device and displays an analysis result, and at least from an input natural sentence, Pattern sentence specifying means for specifying a pattern sentence configured using an analysis item and an expression format for analyzing the log information, and based on the analysis item included in the pattern sentence specified by the pattern sentence specifying means Log information collecting means for collecting log information; and screen control means for generating a screen showing an analysis result in an expression format included in the pattern sentence specified by the log information collecting means.

  Further, as a means for solving the above-mentioned problem, the present invention is a log information analysis visual method for analyzing log information accumulated by operation of an image processing apparatus and displaying an analysis result, wherein an input natural sentence is displayed. A pattern sentence specifying procedure for specifying a pattern sentence configured using at least an analysis item for analyzing the log information and an expression format, and an analysis item included in the pattern sentence specified by the pattern sentence specifying procedure. A log information collecting procedure for collecting the log information on the basis of the log information collecting procedure, and a screen control procedure for generating a screen showing the analysis result by the expression format included in the pattern sentence specified by the log information collecting procedure. .

  Furthermore, as means for solving the above-described problems, the present invention may be a program for causing a computer to execute the procedure in the above-described log information analysis visual method, and a computer-readable storage medium.

  According to the present invention, it is possible to analyze log information by inputting a simple natural sentence and visually display the analysis result.

  Next, the best mode for carrying out the present invention will be described with reference to the drawings.

<Schematic configuration example of the log information analysis visual system>
FIG. 1 is a diagram illustrating a schematic configuration example of a log information analysis visual system according to the present embodiment. As shown in FIG. 1, a log information analysis / visualization system 101 includes a log management / visualization server 100, a management console 103, a PC terminal 104, an image processing apparatus (MFP) 105, a copier 106, and a scanner 107, which are connected to a LAN (Local). It is configured by being connected through a network such as Area Network.

  The log management / visualization server 100 is connected to a plurality of image processing apparatuses (MFPs) 105 and stores various log information accumulated by operating a copy function, a scan function, a print function, a FAX function, and the like included in the image processing apparatus. Accumulate in the log information DB 102. In addition, the log management / visualization server 100 is connected to the copy machine 106 and the scanner machine 107, and also stores various log information stored by operating the respective devices in the log information DB 102.

  The management console 103 is a PC terminal including an input device such as a mouse and a keyboard and an output device such as a display screen, and manages log information accumulated in the log management / visualization server 100.

  The PC terminal 104 is connected to the log management / visualization server 100 and inputs search conditions for analyzing log information accumulated in the image processing apparatus 105, the copier 106, and the scanner 107 on the display screen. Thus, the analysis result of the log information collected according to the search condition is displayed on the display screen.

  With the above-described configuration, the log information analysis / viewing system 101 collects log information accumulated in the image processing apparatus 105, the copier 106, and the scanner 107 in accordance with the purpose of the user, and visually displays the analysis result of the log information. Can be displayed.

  In the present embodiment, the configuration is not limited to the above-described configuration. For example, processing performed on the PC terminal 104 can be performed on the management console. In this case, the PC terminal 104 does not need to be used. Also, log management processing performed by the log management / visualization server 100 can be performed by each MFP or the like.

  Next, the functional configuration of the log information analysis and visualization device according to the present embodiment will be described with reference to FIG.

  The log information analysis / visualization device 100 receives a request to analyze log information accumulated in a plurality of image processing apparatuses, copiers, scanners, etc., by inputting natural sentences by a user, and collects log information according to the request. The analysis result is displayed in a display format that matches the user's request.

  The log information analysis / visualization device 100 includes a screen control unit 10, a sentence analysis unit 20, a sentence learning unit 30, and a log data processing unit 40.

  The screen control unit 10 includes a request receiving unit 11 that receives a user's log information analysis request on how to analyze and visualize log information, and a log display unit that displays a result totaled based on the log information analysis request 12, a processing unit for performing screen display control on a Web browser, for example.

  Here, the request receiving unit 11 generates a screen that receives a user's log information analysis request by inputting a natural sentence in a user's free format. In addition, the request reception unit 11 generates a log information analysis confirmation screen in which settings can be changed based on log information analysis target range items, analysis items, and expression formats extracted by analyzing a user's natural sentence. The request reception unit 11 receives a log information analysis request from the user from these generated screens.

  The log display unit 12 displays the analysis result of the collected log information using an expression format such as a bar graph, a pie graph, or a table according to a user request. Accordingly, the analysis result can be easily visually expressed in an expression format suitable for the purpose without forcing the user to perform complicated search conditions and input work for analyzing log information.

  The sentence analysis unit 20 analyzes a natural sentence in a free format input by the user, and clarifies an analysis item for analyzing log information intended by the user and a display format for displaying the analyzed result. Is a processing unit. The sentence analysis unit 20 includes a context analysis unit 21, a pattern management unit 22, and a natural sentence search processing unit 23.

  The context analysis unit 21 extracts a part corresponding to the analysis target range item of the log information from the natural sentence input by the user to the request reception unit 11 of the screen control unit 10 and separates it from the natural sentence. Here, the analysis target range items include, for example, “period”, “type of image processing function”, “user who operated the image processing apparatus”, “image processing apparatus”, “similar document ID”, “scan destination”, and the like. This refers to limiting the scope of collected log information.

  The context analysis unit 21 refers to the synonym dictionary 24 stored in advance, extracts vocabulary, characters, words, and the like that are considered analysis target range items from the natural sentence input by the user, and separates them from the natural sentence. For example, the context analysis unit 21 extracts proper nouns included in natural sentences such as “in the past three months”, “in March 2008”, and “document category is personnel document” input by the user, and synonyms It is determined using the dictionary 24 whether or not the analysis target range item is applicable.

  The context analysis unit 21 separates the vocabulary determined to correspond to the analysis target range item from the input natural sentence, and manages the separated vocabulary separately. This separated vocabulary is used when collecting log information. In this way, by separating the vocabulary that is the analysis target range item from the natural sentence, it becomes easy to identify the pattern sentence corresponding to the natural sentence performed in the natural sentence search processing unit 23. Details of the analysis target range item will be described later.

  The pattern management unit 22 extracts a pattern item from the pattern ID of the pattern sentence specified by the natural sentence search processing unit 23. Here, the pattern item is, for example, a main item and a sub item that constitute a pattern sentence and are analysis items in collecting log information, an expression format, and the like. Further, the pattern management unit 22 collects log information based on the pattern items, and extracts a processing method for displaying based on the expression format.

  Here, the main item as an analysis item is an aggregation target for the purpose of analysis of log information, and indicates, for example, “number of logs”, “log ratio”, “number of violations”, “number of valid cases”, and the like. The sub-items that are analysis items are items for further classifying the aggregated main items. For example, items such as “by year”, “by month”, “by user”, and “by scan destination” Show.

  Here, the expression format is a format for visually indicating the analysis result of the log information, and indicates, for example, “bar graph”, “pie graph”, “table”, and the like.

  In addition, the processing method here is a processing method for collecting log information based on analysis items and displaying the result of aggregation. For example, “divide the log of the target range by year and the number of logs in each year And a bar graph is created with the year on the horizontal axis and the number of logs on the vertical axis.

  The pattern management unit 22 refers to the pattern management unit 25 that is a combination of the above-mentioned “main item”, “sub-item”, “expression form”, and “processing method”, which are pattern items, and is stored as a table. A pattern item and a processing method are extracted from the pattern ID of the specified pattern sentence. Details of the pattern management table 25 will be described later.

  The natural sentence search processing unit 23 is a processing unit that identifies a pattern sentence corresponding to a natural sentence in which a portion corresponding to the analysis target range is separated from the natural sentence input by the context analysis unit 21. In specifying the pattern sentence, the natural sentence search processing unit 23 refers to the natural sentence database 26.

  The natural sentence database 26 assumes a plurality of input sentences corresponding to the main item, sub-item, and expression form that the user is likely to input, and stores a pattern sentence that combines the main item, sub-item, and expression form. It is. Details of the natural sentence database 26 will be described later.

  The sentence learning unit 30 is a processing unit that registers a plurality of sentences corresponding to each pattern sentence stored in advance in the natural sentence database 26 by learning, and shares the natural sentence search processing unit 23. Thereby, the natural sentence search processing unit 23 can specify the pattern sentence corresponding to the input natural sentence based on the pattern sentence registered by the sentence learning unit 30.

  The log data processing unit 40 is based on the log data 41 in which log information of a plurality of image processing apparatuses (MFPs), copiers, scanners, and the like is accumulated based on the processing method and analysis target range extracted by the sentence analysis unit 20. It is a processing unit that collects log information and determines a value for displaying the analyzed result based on the expression format.

<Hardware configuration>
Next, a hardware configuration example of the log information analysis / visualization device 100 will be described with reference to FIG. FIG. 3 is a diagram illustrating an example of a hardware configuration of the log information analysis and visualization device.

  In FIG. 3, the log information analysis / visualization device 100 is a computer device, and includes an input device 51, an output device 52, a drive device 53, and an auxiliary storage device 54 that are connected to each other via a system bus. , A memory device 55, an arithmetic processing device 56, and an interface device 57.

  The input device 51 includes a keyboard and a mouse, and is used to input various signals. The output device 52 includes a display device and is used to display various windows and data. The interface device 57 includes a modem, a LAN card, and the like, and is used for connecting to a network.

  The log information analyzing / viewing apparatus 100 acquires various log information from a plurality of image processing apparatuses (MFPs), copiers, scanners, and the like provided outside via the network by the interface device 57. Further, the log information analysis / viewing apparatus 100 outputs the analysis result according to the display format to the management console 103 and the PC terminal 104 provided outside via the network.

  The log information analysis visual program according to the present embodiment is at least a part of various programs that control the log information analysis visual device 100. The log information analysis visual program is provided by, for example, distribution of the storage medium 58 or downloading from a network. In addition, the storage medium 58 storing the log information analysis / viewing program is a storage medium such as a CD-ROM, a flexible disk, a magneto-optical disk, or the like that stores information optically, electrically, or magnetically, or a ROM (Read Only Memory). ), And can be provided using various types of storage media such as a semiconductor memory that electrically stores information, such as a flash memory.

  When the storage medium 58 storing the log information analysis / visible program is set in the drive device 53, the log information analysis / visible program is installed from the storage medium 58 to the auxiliary storage device 54 via the drive device 53.

  Further, the log information analysis visual program may be downloaded from the network and installed in the auxiliary storage device 54 via the interface device 57.

  The log information analysis / visualization apparatus 100 stores the installed log information analysis / visualization program and also stores necessary files, data, and the like. The memory device 55 reads and stores the log information analysis visible program from the auxiliary storage device 54 at the time of activation. The arithmetic processing unit 56 implements various processes as described later according to the log information analysis / visible program stored in the memory device 55.

<About accumulated log information>
Next, log information stored in the image processing apparatus or the like will be described with reference to FIG. FIG. 4 is a diagram illustrating an example of log information stored in the image processing apparatus.

  As shown in FIG. 4, log information accumulated in the image processing apparatus includes, for example, “year / month / date / time”, “user”, “image processing function type”, “success / failure”, “number of paper outputs”, “MFP name”. ”,“ MFP IP address ”,“ document category ”,“ similar document ID ”,“ policy determination result ”,“ print source PC address ”,“ scan destination ”,“ FAX transmission destination ”,“ FAX transmission source ”, etc. is there.

  Here, “year / month / date / time” indicates, for example, the date / time when the image processing apparatus is operated. The “function type” indicates, for example, a copy function, a print function, a FAX transmission / reception function, a scan function, etc. as functions of the image processing apparatus (MFP). “Success / failure” indicates, for example, whether the processing of the image processing function based on a user instruction has succeeded or failed (error). Here, the “paper output number” indicates the number of sheets copied by the copy function, for example.

  “MFP name” indicates, for example, the host name of the image processing apparatus (MFP) operated by the user. “MFP IP address” indicates, for example, an IP address of an image processing apparatus or the like operated by a user. The “document category” indicates a category of an image document obtained as a result of content analysis of an image that has been subjected to image processing such as printing by a user.

  The “similar document ID” indicates a similar document ID that is estimated from the attributes attached to the already learned document, for example, as a result of content analysis of an image printed by the user. The “policy determination result” indicates a result of the policy determination based on the category of the image document, the executor, the function, and the like, and whether the result is valid or violated.

  The “print source PC address” indicates, for example, the IP address of the client PC that the user has issued a print instruction at the time of printing. “Scan destination” indicates, for example, an E-mail address of a destination scanned by the user at the time of scanning, a destination name, and the like. “FAX transmission destination” indicates, for example, the FAX number of the transmission destination at the time of FAX transmission. “FAX transmission source” indicates, for example, the FAX number of the transmission source at the time of FAX reception.

  Various types of log information as described above are recorded and stored as the image processing apparatus is operated.

<Example 1 of target free entry screen>
Next, a target free input screen in which a log information analysis request is input in a natural sentence by a user when collecting and analyzing log information will be described with reference to FIG. FIG. 5 is a diagram illustrating an example of a target free input screen using natural sentences.

  As shown in FIG. 5, for example, the target free entry screen 110 has “Please describe the target display in text.” In the input part, the user indicates “the number of fraudulent activities in days. A log information analysis request such as “graph” can be freely input in natural sentences.

  By using the target free input screen 110, the user can input a log information analysis request for collecting log information using a simple natural sentence in a free format without inputting complicated search conditions. Can be directed.

  In addition, when the confirmation button on the target free input screen 110 is executed, a log information analysis visual process, which will be described later, is started based on the input log information analysis request in the natural sentence.

<Example 1 of target confirmation screen>
Next, a target confirmation screen (log information analysis confirmation screen) derived from the natural sentence input by the user in FIG. 5 will be described with reference to FIG. FIG. 6 is a diagram illustrating an example of the target confirmation screen.

  In the target confirmation screen of FIG. 6, the content derived based on the natural sentence “graph indicating the number of fraudulent activities in units of days” input by the user on the target free input screen 110 of FIG. 5 is input in advance. It is displayed in the state that was done.

  For example, as shown in FIG. 6, the “number of violations” in the main item portion from the characters “number of fraudulent acts” in the input natural sentence is changed from the word “daily” in the natural sentence to “day” in the subitem portion. “Other” is displayed by deriving the “line graph” of the expression item portion from the word “graph” of the natural sentence.

  In addition, the target confirmation screen 111 includes “period”, “function”, “success / error”, “user”, “MFP”, “document category”, “similar document ID”, “ There are items such as “scan destination”, “FAX transmission destination”, and “FAX transmission source”, and corresponding contents are displayed based on a natural sentence input by the user. If there is no content corresponding to the input natural sentence, “None” is selected and displayed.

  In addition, the target confirmation screen 111 has “The following display is performed based on the data in the analysis target range.” As described above, the analysis items of the log information are “main item” and “sub item”. In addition, for the “expression” item, the corresponding contents are displayed in advance based on the natural sentence input by the user.

  In the target confirmation screen 111, defaults can be applied to items that are not in the input natural sentence and ambiguous expressions.

  As described above, by using the target confirmation screen 111, the user can confirm the content of the log information analysis request read from the natural sentence input on the target free input screen 110. This makes it possible to analyze the target log information and visualize the result by a graph or the like more accurately and without performing complicated input.

  Each item displayed on the target confirmation screen 111 can be changed by the user, and in this case, the user can select an arbitrary parameter from parameters preset for each item using a table or the like. For this purpose, for example, a selection function such as a combo box is used.

  In addition, when the execution button of the target confirmation screen 111 is executed, log information analysis visible processing described later is performed based on the content of the confirmation screen.

  Furthermore, the layout, font, and the like of each item displayed on the target confirmation screen 111 shown in FIG. 6 are not particularly limited in the present invention.

<Example 1 of analysis result displayed in specified expression format>
Next, an example of the analysis result displayed in the expression format designated by the user will be described with reference to FIG. FIG. 7 is a diagram illustrating an example of the analysis result displayed in the designated expression format.

  As shown in FIG. 7, based on the contents of the log information analysis request as “daily line graph of the number of violations in the period from January 1, 2008 to the present” on the target confirmation screen 111 in FIG. The analysis result of the analyzed log information is displayed as a graph 112.

  The graph 112 shows the number of violations on the vertical axis and the day on the horizontal axis, and corresponds to the main item “number of violations” and the sub-item “daily” specified on the target confirmation screen 111 of FIG. .

  In this way, the user can analyze the log information intended by the user by specifying analysis items on the target confirmation screen without complicated input, etc., and easily graph the analysis results Is possible.

<Example 2 of target free entry screen>
Next, a target free input screen in which a log information analysis request is input by a user in order to collect and analyze log information will be described with reference to FIG. FIG. 8 is a diagram illustrating an example of a target free input screen using natural sentences.

  As shown in FIG. 8, for example, the user can freely enter a natural sentence such as “the number of documents printed and scanned last month” in the input portion of the target free input screen 113.

  In addition, when the confirmation button on the target free input screen 113 is executed, a log information analysis visual process described later is started based on the input log information analysis request in the natural sentence.

<Example 2 of target confirmation screen>
Next, a target confirmation screen (log information analysis confirmation screen) derived from the natural sentence input by the user in FIG. 8 will be described with reference to FIG. FIG. 9 is a diagram illustrating an example of the target confirmation screen.

  In the target confirmation screen 114 of FIG. 9, the content derived based on the natural sentence “the number of documents printed and scanned last month” input by the user on the target free input screen 113 of FIG. It is displayed in the state that was done.

  For example, as estimated from “last month” of the input natural sentence, “2008/05/01 to 2008/05/31” is displayed in the “period” of the target range item as shown in FIG. In addition, as shown in FIG. 9, “continuation of printing and scanning” is displayed in the “function” of the target range item, as estimated from “printing and scanning” of the input natural sentence.

  In addition, as shown in FIG. 9, the sub-items that are analysis items are “by similar document ID” and the expression items are “bar graph” as defaults, as estimated from the “number of documents” of the input natural sentence. Is displayed.

  As described above, by using a function such as learning in advance, when a specific vocabulary is input on the target free input screen 114, it is reflected in the analysis target range item on the target confirmation screen, or is displayed as a default on a sub-item or the like. You can make it. As a result, it is possible to execute log analysis more quickly and display the total result.

  Each item displayed on the target confirmation screen 114 can be changed by the user, and in this case, the user can select an arbitrary parameter from parameters set in advance by a table or the like for each item. For example, a selection function such as a combo box is used.

  In addition, when the execution button of the target confirmation screen 114 is executed, log information analysis / visible processing described later is performed based on the content of the confirmation screen.

  Furthermore, the layout, font, and the like of each item displayed on the target confirmation screen 114 shown in FIG. 9 are not particularly limited in the present invention.

<Example 2 of analysis result displayed in specified expression format>
Next, an example of the analysis result displayed in the expression format designated by the user in FIG. 9 will be described with reference to FIG. FIG. 10 is a diagram illustrating an example of the analysis result displayed in the designated expression format.

  As shown in FIG. 10, “similar document IDs for the number of logs printed and scanned continuously during the period from May 1, 2008 to May 31, 2008” on the target confirmation screen 114 in FIG. The analysis result of the analyzed log information is displayed as a graph 115 based on the content requested to analyze the log information as “display bar graph”.

  In the graph 115, the vertical axis indicates the number of logs, and the horizontal axis indicates the similar document ID. The main item “number of logs” and the sub-item “by similar document ID” specified on the target confirmation screen 114 in FIG. It corresponds.

  In this way, the user also displays the default items on the target confirmation screen for items that were not entered in the target free input. Therefore, the user can analyze the log information intended by the user using the default display, and easily display the analysis results in a graph. Can be realized.

<Example 3 of target free entry screen>
Next, a target free input screen in which a log information analysis request is input by a user in order to collect and analyze log information will be described with reference to FIG. FIG. 11 is a diagram illustrating an example of a target free input screen using natural sentences.

  As shown in FIG. 11, for example, the user can freely input a natural sentence such as “display of a log printed and scanned for the past month” in the input portion of the target free input screen 116.

  In addition, when the confirmation button on the target free input screen 116 is executed, log information analysis / visible processing described later is started based on the input natural sentence.

<Example 3 of target confirmation screen>
Next, a target confirmation screen (log information analysis confirmation screen) derived from the natural sentence input by the user in FIG. 11 will be described with reference to FIG. FIG. 12 is a diagram illustrating an example of the target confirmation screen.

  In the target confirmation screen 117 of FIG. 12, the content derived based on the natural sentence “Display of log printed and scanned for the past month” input by the user on the target free input screen 116 of FIG. , Displayed in a pre-input state.

  For example, “2008/05/01 to present” is displayed in the “period” of the analysis target range item, as shown in FIG. 12, estimated from “here 1 month” of the input natural sentence. In addition, as shown in FIG. 12, “continuation of printing and scanning” is displayed in the “function” of the analysis target range item as estimated from “printing and scanning” of the input natural sentence.

  In addition, as shown in FIG. 12, the sub-items to be analyzed are “by similar document ID” and the expression items are “by similar document ID”, as estimated from the “display of printed and scanned logs” of the input natural sentences. Table "is displayed as the default.

  As described above, by using a function such as learning in advance, when a specific vocabulary is input on the target free input screen 116, it is reflected in the analysis target range item on the target confirmation screen, or is displayed as a default on a sub-item or the like. You can make it. As a result, it is possible to execute log analysis more quickly and display the total result.

  Each item displayed on the target confirmation screen 117 can be changed by the user, and in this case, the user can select an arbitrary parameter from parameters set in advance by a table or the like for each item. For example, a selection function such as a combo box is used.

  Further, by executing the execution button of the target confirmation screen 117, a log information analysis / visible process described later is performed based on the content of the confirmation screen.

  Furthermore, the layout, font, and the like of each item displayed on the target confirmation screen 117 shown in FIG. 12 are not particularly limited in the present invention.

<Example 3 of analysis result displayed in specified expression format>
Next, an example of the analysis result displayed in the expression format designated by the user shown in FIG. 12 will be described with reference to FIG. FIG. 13 is a diagram illustrating an example of the analysis result displayed in the designated expression format.

  As shown in FIG. 13, “display a table by similar document IDs for logs that have been continuously printed and scanned in the period from May 1, 2008 to the present” on the target confirmation screen 117 in FIG. The analysis result of the analyzed log information is displayed in Table 118 based on the requested log information analysis.

  The table 118 includes items of “operation date / time”, “user”, “similar document ID”, “function”, “success / failure”, “scan destination”, and “print source PC”, and a log history is displayed for these items. Has been. “Scan destination” and “print source PC” in Table 118 are related information that is automatically added when the words “print” and “scan” are extracted in “function”.

  In this way, the user can analyze the log information intended by the user by specifying analysis items on the target confirmation screen without complicated input, etc., and easily tabulate the analysis results Is possible.

<Log analysis processing procedure: first embodiment>
Next, the first example of the log analysis processing procedure in the present embodiment will be specifically described with reference to a sequence flowchart with reference to FIG.

  FIG. 14 is a sequence flowchart showing a first embodiment of the log analysis processing procedure. In the first embodiment, regarding the log information analysis request input by the natural sentence from the user, the corresponding pattern item and analysis target range item described above are displayed to the user on the confirmation screen (target confirmation screen), and the user The log collection processing is performed after the execution instruction is given from the above, and the collection result is presented in a predetermined display format.

  In addition, the sequence flowchart illustrated in FIG. 14 includes an image control unit 10, a sentence analysis unit 20, a context analysis unit 21, a pattern management unit 22, a natural sentence search processing unit 23, and a log data processing unit 40 in the log information analysis and visualization apparatus 100. Shows a log analysis processing procedure.

  First, when a target free input screen for allowing a user to input a search condition using a natural sentence is displayed, the natural sentence is input from the user. In the example of FIG. 14, a natural sentence “the number of documents printed and scanned last month” is input.

  When a natural sentence is input to the target input screen by the user, the screen control unit 10 outputs the natural sentence input to the sentence analysis unit 20 (S11). The sentence analysis unit 20 analyzes the input natural sentence. Specifically, the sentence analysis unit 20 sends an extraction request for the analysis target range item to the context analysis unit 21 (S12), and the context analysis unit 21 performs extraction using the synonym dictionary 24 (S13). Next, the context analysis unit 21 outputs the extracted analysis target range item to the sentence analysis unit 20 (S14). Examples of the analysis target range item include “last month” and “print and scan”. .

  Next, the sentence analysis unit 20 outputs a pattern sentence specifying request to the natural sentence search processing unit 23 for the natural sentence in which the extracted analysis target range item is separated from the input natural sentence (S15). In the example of FIG. 14, a natural sentence “the number of documents printed and scanned” is output.

  Next, the natural sentence search processing unit 23 performs a natural sentence search using the natural sentence DB 26 in response to the output pattern sentence specifying request (S16), specifies a pattern sentence corresponding to the separated natural sentence, The pattern ID of the specified pattern sentence is acquired (S17). In addition, the natural sentence search processing unit 23 outputs the acquired pattern ID to the sentence analysis unit 20 (S18).

  Next, the sentence analysis unit 20 outputs a pattern item extraction request to the pattern management unit 22 based on the pattern ID obtained in the process of S18 (S19). The pattern management unit 22 performs pattern search using the pattern management DB 25 based on the obtained pattern ID (S20), and outputs the searched pattern item to the sentence analysis unit 20 (S21). As examples of pattern items, for example, “main item” is the number of logs, “sub item” is classified by similar document ID, and “expression” is a bar graph or the like.

  Next, the sentence analysis unit 20 outputs the analysis target range item obtained by the process of S14 and the pattern item obtained by the process of S21 to the screen control unit 10 (S22). The screen control unit 10 generates and displays a confirmation screen based on the pattern item and analysis target range item obtained by the process of S24, and according to the execution instruction input by the user, the pattern item and analysis target range item. Is output to the sentence analysis unit 20 (S23). At this time, the sentence analysis unit 20 re-determines the pattern ID (S24).

  Next, the sentence analysis unit 20 outputs a processing ID acquisition request to the pattern management unit 22 based on the confirmed pattern ID (S25), and the pattern management unit 22 performs a pattern search again using the pattern management DB 25 (S26). The process ID is acquired (S27). The pattern management unit 22 outputs the acquired process ID to the sentence analysis unit (S28).

  The sentence analysis unit 20 performs a process according to the process ID obtained by the process of S28 (S29). The sentence analysis unit 20 performs log collection processing (analysis target range item, request according to the process ID) for the log data processing unit 40 as processing according to the process ID (S30). That is, the log data processing unit 40 collects the corresponding log from the log data 41 based on the analysis target range item and the process ID obtained by the processing of S30, and outputs the collection result to the sentence analysis unit 20. (S31). The sentence analysis unit 20 makes a display request (display data list, display format) to the screen control unit 10 based on the collection result obtained by the process of S31 (S32). The screen control unit 10 generates a screen based on the display request obtained by the process of S32 and displays it to the user.

<Log analysis processing procedure: second embodiment>
Next, a second example of the log analysis processing procedure in the present embodiment will be described specifically using a sequence flowchart with reference to FIG.

  FIG. 15 is a sequence flowchart showing a second embodiment of the log analysis processing procedure. In the second embodiment, as compared with the first embodiment described above, the corresponding pattern item and analysis target range item described above corresponding to the log information analysis request input by the user in the natural sentence are confirmed with the user. When the user changes the content after being displayed on the screen and is instructed to execute it, log collection processing is performed based on the changed content of the instruction, and the collection result is presented in a predetermined display format.

  Accordingly, the processing from S41 to S52 shown in FIG. 15 is equivalent to the processing from S11 to S22 in the first embodiment shown in FIG. 14 described above, and a specific description thereof will be omitted here.

  In the second example of the log analysis processing procedure shown in FIG. 15, the screen control unit 10 generates and displays a confirmation screen based on the pattern item and the analysis target range item obtained by the processing of S52. Thereafter, the user inputs an instruction to change the contents of at least one of the pattern items and analysis target range items necessary for the log collection processing. The log collection contents can be changed by using a target confirmation screen as shown in FIG. 6, FIG. 9, or FIG. Changes can be made by selecting using the selection function.

  Next, the pattern item and the analysis target range item are output to the sentence analysis unit 20 in accordance with the execution instruction input with the contents changed by the user (S53). At this time, the sentence analysis unit 20 re-determines the pattern ID (S54).

  Next, the sentence analysis unit 20 outputs a processing ID acquisition request to the pattern management unit 22 based on the confirmed pattern ID (S55), and the pattern management unit 22 performs pattern search again by the pattern management DB 25 (S56). The process ID is acquired (S57). The pattern management unit 22 outputs the acquired process ID to the sentence analysis unit 20 (S58).

  The sentence analysis unit 20 performs a process according to the process ID obtained by the process of S58 (S59). Further, the sentence analysis unit 20 performs log collection processing (analysis target range item, request according to the process ID) on the log data processing unit 40 as a process according to the process ID (S60). That is, the log data processing unit 40 collects a corresponding log from the log data 41 based on the analysis target range item and the processing ID obtained by the processing of S60, and outputs the collection result to the sentence analysis unit 20. (S61). The sentence analysis unit 20 makes a display request (display data list, display format) to the screen control unit 10 based on the collection result obtained by the process of S33 (S62). The screen control unit 10 generates a screen based on the display request obtained by the process of S62 and displays it to the user.

<Example of analysis target range item extraction procedure>
Next, the analysis target range item extraction procedure in the present embodiment will be specifically described with reference to a flowchart with reference to FIG. FIG. 16 is a flowchart showing an example of the analysis target range item extraction procedure in the present embodiment.

  In FIG. 16, the context analysis unit 21 searches for a vocabulary specifying “period” from the input natural sentence (S71). Next, the context analysis unit 21 refers to the synonym dictionary 24 to determine whether or not a vocabulary specifying “period” exists in the natural sentence (S72).

  If there is a vocabulary specifying “period”, the period is specified (S73). In specificization of a period, a part corresponding to a “period” is separated from an input natural sentence, and the separated part is stored in a predetermined storage area.

  If the vocabulary does not exist in the process of S72, or after the process of S73 ends, the vocabulary specifying the “user” is searched from the input natural sentence (S74). Next, it is determined whether or not there is a vocabulary specifying “user” in the natural sentence (S75).

  If there is a vocabulary specifying “user” (YES in S75), the user is instantiated (S76). That is, a part corresponding to “user” is separated from the input natural sentence, and the separated part is stored in a predetermined storage area.

  Also, in the process of S75, if there is no vocabulary, or after the process of S76 ends, the analysis target range item extraction procedure ends. Through the processing described above, the analysis target range item is extracted from the natural sentence input by the user.

  Note that the analysis target range item extraction procedure described above is performed by performing a similar search on the vocabulary specifying each of the analysis target range items such as function, success / failure, and MFP name. The portion corresponding to the analysis target range item stored in the storage area is generated when the screen control unit 10 generates a target confirmation screen, which is a log information analysis confirmation screen, and the sentence analysis unit 20 performs log information collection processing. Used for

<Pattern sentence identification processing procedure>
Next, a specific example of the pattern sentence specifying process procedure will be described with reference to a flowchart. FIG. 17 is a flowchart illustrating an example of a pattern sentence specifying process procedure in the present embodiment.

  In FIG. 17, the natural sentence search processing unit 23 searches the natural sentence data DB 26 stored in advance for the natural sentence obtained by separating the vocabulary corresponding to the analysis target range item from the natural sentence input by the user (S 81). The search result is checked to see if there is a corresponding pattern sentence (S82).

  In the process of S82, if there is a search result, the pattern ID is acquired from the most similar record in the ranking among the corresponding pattern sentences (S83). In the process of S82, if there is no search result, pattern = NULL (determination not possible) is set (S84).

  Further, after the processes of S83 and S84 are completed, the pattern value is output to the sentence analysis unit 20 (S85), and the process is terminated.

  Through the above-described processing, the pattern sentence corresponding to the natural sentence from which the vocabulary corresponding to the analysis target range item is separated is specified. An example of pattern sentences stored in the natural sentence data DB 26 will be described later.

<Example of processing procedure according to processing ID>
Next, a processing procedure example according to the processing ID corresponding to the processing of S29 and S59 described above will be described with reference to FIGS. On the target free entry screen, the user inputs “Number of documents scanned and printed last month” and displayed on the target confirmation screen “Number of continuous operation logs of last month's print / scan” converted into a bar graph for each similar document ID. It is assumed that the execution instruction is made with the content of "."

<Example of processing procedure according to processing ID in sentence analysis unit>
First, the processing procedure according to the processing ID in the sentence analysis unit 20 will be described using a flowchart with reference to FIG. FIG. 18 is a flowchart illustrating an example of a processing procedure according to the processing ID in the sentence analysis unit.

  In the process illustrated in FIG. 18, the sentence analysis unit 20 acquires condition A “period condition” of the analysis target range item corresponding to the process ID (S91). Here, as the period condition, for example, a specific from date / time and to date / time are determined from “last month”.

  Next, the sentence analysis unit 20 acquires condition B “function condition” of the analysis target range item (S92). Here, for example, “print”, “scan”, and “continuous condition” are determined from “printed and scanned” as functional conditions.

  Next, the sentence analysis unit 20 acquires the number of logs satisfying the condition A acquired by the process of S91 from the log data processing unit 40 and the condition B acquired by the process of S92 for each similar document ID (S93). ).

  Next, the sentence analysis unit 20 requests the screen control unit 10 to display a bar graph that is an expression format designated based on the list of “similar document IDs, number of cases” (S94), and ends the processing. .

<Example of log information collection processing in the log data processing unit>
Next, an example of a log information collection processing procedure in the log data processing unit 40 will be described using a flowchart with reference to FIG. FIG. 19 is a flowchart illustrating an example of a log information collection processing procedure in the log data processing unit.

  In the process shown in FIG. 19, first, the log data processing unit 40 selects from date and time of condition A, to date and time of condition A, “print” and “scan” of condition B from all log information of log data 41 accumulated in advance. ”Is searched (S101).

  Next, the log list of search results obtained in the process of S101 is grouped by “similar document ID” (S102), and the process described later is performed for each grouping unit. Here, the log data processing unit 40 extracts the features of each document by using, for example, a similar document database stored in advance, estimates similar documents based on the extracted features, and for each similar document. Can be grouped. In this way, by grouping for each similar document ID, it is possible to group the logs of documents that have undergone both “print” and “scan” processing.

  Next, it is determined whether or not the log information collection processing is completed for all the grouped groups (S103). If the processing is not completed, a continuous log set list is acquired (S104). The number of cases is acquired from the list length of the obtained list (S105).

  Further, the information is added to the list of similar document ID and number information ({similar document ID, number}) (S106), and the process returns to S103.

  If the log information collection processing is completed for all groups in the processing of S103, a list of similar document IDs and information on the number of cases ({similar document ID, number of cases}) is output (S107), and the processing ends. To do.

<Specific example of continuous log set list>
Next, a specific example of the continuous log set list acquired by the process of S104 described above will be described with reference to the drawings. FIG. 20 is a diagram illustrating an example of a continuous log set list.

  As shown in FIG. 20, the continuous log set includes a plurality of log records having different items (functions), and one item (function) is accumulated in one record. For example, in the example of the continuous log set shown in FIG. 20, one print log record and a plurality of scan log records are accumulated.

  Thus, in the process of S104 shown in FIG. 19 described above, an array list having the structure shown in FIG. 20 is acquired.

<Example of continuous log extraction processing procedure>
Next, with reference to FIG. 21, the continuous log extraction process procedure of the continuous log set list acquired in the process of S104 of FIG. 19 will be described using a flowchart. FIG. 21 is a flowchart illustrating an example of a continuous log extraction processing procedure in the log data processing unit. Note that the processing shown in FIG. 21 is performed, for example, as shown in the continuous log set list of FIG. An example of generating a set list is shown.

  In the process shown in FIG. 21, first, the log data processing unit 40 sequentially acquires one log record from the log information grouped for each similar document ID in the process of S102 of FIG. 19 (S111). It is determined whether the record is over (S112).

  Here, if the record is not the end, it is next determined whether or not it is a print log (in this embodiment, it is “scan log” when it is not “print log”) (S113).

  In the process of S113, if it is a print log, it is next determined whether or not there is an existing continuous log set candidate (S114).

  If there is an existing continuous log set candidate, it is next determined whether or not the content of the continuous log set candidate is substantial (S115). Here, whether or not the content of the continuous log set candidate is substantial is determined by, for example, extracting the continuous log “printed” and “scanned” shown in FIG. If there is, the “print log” and the “print log” are continuous, so it is determined that the content of this continuous log set candidate is not substantial.

  In the process of S115, if the contents of the continuous log set candidates are substantial, the existing contents are added to the continuous log set list (S116).

  Further, in the process of S115, if the content of the continuous log set candidates is not fulfilled, or after the process of S116 is completed, the existing continuous log set candidates are deleted (S117). Next, a continuous log set candidate is newly generated, a print log is set (S118), and the process returns to S111.

  In the process of S113, if it is not a print log, it is determined as a scan log, and it is determined whether there is an existing continuous log set candidate (S119). Here, when there is an existing continuous log set candidate, the time with the previous log is compared (S120), and it is determined whether the continuous time is within a specified range (S121). The above-mentioned specified range is specified in advance as a system parameter value.

  In the process of S121, when the continuous time is within the specified range, the scan log is set to the continuous log set candidate (S122), and the process returns to S111. In the processing of S121, if the continuous time is not within the specified range, it is determined whether or not the content of the continuous log set candidate is substantial (S123). If the content is substantial, the continuous log set list is entered. Existing contents are added (S124).

  Also, in the process of S123, if the content of the continuous log set candidates is not enriched, or after the process of S124 is completed, the existing continuous log set candidates are deleted (S125), and the process returns to S111.

  If there is no continuous log set candidate in the process of S119, the process returns to S111. If the record ends in the process of S112, a continuous log set list is output (S126), and the process ends.

  Through the above-described processing, the log data processing unit 40 can extract a plurality of processes “print and scan” as a series of processes. In addition, by applying the processing described above, it is possible to acquire not only “print” and “scan” items (functions) but also continuous logs of other items (functions), and more than two types of items. (Function) can also be acquired as a continuous log by arbitrarily combining them.

<Example of analysis target range item>
Next, an analysis target range item for collecting and analyzing log information extracted from a natural sentence will be described with reference to FIG. FIG. 22 is a diagram illustrating an example of the analysis target range item.

  According to FIG. 22, the identification information ID is set in the analysis target range item. For example, the “period”, “function”, “success / failure”, “user”, “MFP”, “Document category”, “similar document ID”, “scan destination”, “FAX transmission destination”, “FAX transmission source”, and the like are set.

  Here, the “period” refers to, for example, a log corresponding to a period, and a log corresponding to the start or end of the period. “Function” refers to a log limited by functions such as a copy function, a print function, a scan function, and a FAX function of an image processing apparatus. The “success / failure” is, for example, a log limited by success / error such as a copy function of the image processing apparatus. The “user” is, for example, a log whose users are limited by a user name or the like.

  Further, “MFP” refers to a log in which the MFP is limited by the name of the MFP, for example. The “document category” is, for example, a log in which the document category is limited by the document category name. The “similar document ID” is, for example, a log limited by a similar document ID or the like in cooperation with document management. The “scan destination” is, for example, a log whose destination after scanning is limited by a destination name, an E-mail address, or the like.

  In addition, the “FAX transmission destination” is, for example, a log in which the FAX transmission destination is limited by a FAX number and a destination name. The “FAX transmission source” is, for example, a log in which the FAX transmission source is limited by a FAX number and a destination name.

  Each item of the analysis target range described above is extracted from the natural sentence input by the user by the context analysis unit 21 of the sentence analysis unit 20 and displayed on the target confirmation screen.

<Example of analysis item>
Next, analysis items for analyzing log information will be described with reference to FIGS. 23 and 24. FIG. 23 is a diagram illustrating an example of main items constituting analysis items. FIG. 24 is a diagram illustrating an example of sub-items constituting the analysis item.

  As shown in FIG. 23, IDs are set for the main items. For example, for the IDs such as symbols b1 to b9, “number of logs”, “log ratio”, “number of violations”, “number of valid cases”, “validity / violation” “Ratio”, “Error count”, “Success count”, “Success / error ratio”, and “Paper output ratio” are set.

  Here, the “number of violations” indicates the number of violations determined to be violations based on the policy determination result such as whether a confidential document has been copied, for example. The “number of valid cases” indicates, for example, that the policy determination result is a violation. Indicates the number of cases not. The “legitimate / violation ratio” indicates, for example, the ratio of the number of cases in which the policy determination result or the like is not violation or violation.

  The “number of errors” indicates, for example, the number of operation results of the copy function, etc., and the “number of successful cases” indicates, for example, the number of operation results of the copy function, etc. that are not errors. Indicates, for example, the total number of paper output such as the target log.

  Next, as shown in FIG. 24, the sub-item is set by the ID. For example, for the IDs such as symbols c1 to c13, “by year”, “by month”, “by day”, “by hour”, “hour” By band, by function, by user, by MFP, by document category, by similar document ID, by scan destination, by fax destination, by fax source "Is set. Moreover, the combination item of c1-c13 can be set to a subitem.

<Example of expression format>
Next, an expression format for displaying the analysis result will be described with reference to FIG. FIG. 25 is a diagram illustrating an example of an expression format for displaying an analysis result.

  As shown in FIG. 25, an ID is set as an expression format. For example, “bar graph”, “pie graph”, “line graph”, “radar chart”, “table”, etc. are assigned to IDs such as symbols d1 to dN. Is set.

  The above-described items shown in FIGS. 23 to 25 are extracted from the natural sentences input by the user by the processes of the context analysis unit 21, the natural sentence search processing unit 23, and the pattern management unit 22 of the sentence analysis unit 20. Displayed on the target confirmation screen.

<Example of pattern management table>
Next, the pattern management table 25 including analysis items, expression formats, and processing methods will be described with reference to FIG. FIG. 26 is a diagram illustrating an example of a pattern table.

  According to FIG. 26, the main item, sub-item, and expression format in which the above-described ID is set are combined, and a pattern ID is set for each combination. A processing method is set for each pattern ID.

  For example, the pattern ID “1” is combined by the main item “b1”, the sub-item “c1”, and the expression format “d1”, and the processing ID “func1” of the processing method is set. The processing ID “func1” indicates a processing method for dividing the logs in the target range by “year”, totaling the number of logs for each year, and creating a bar graph with the year as the horizontal axis and the number as the vertical axis. .

  For example, the pattern ID “2” is combined by the main item “b1”, the sub-item “c1”, and the expression format “d2”, and the processing ID “func2” is set. The processing ID “func2” indicates a processing method for creating a pie chart for each year by dividing the logs in the target range by “year” and totaling the number of logs for each year.

  The main item, sub-item, and expression format items described above are extracted from the natural text input by the user by the natural text search processing unit 23 and the pattern management unit 22 of the text analysis unit 20 and are displayed on the target confirmation screen. Is displayed. Also, the processing method shown in FIG. 26 is extracted by the pattern management unit 22 based on the execution instruction of the target confirmation screen by the user, and is executed by the log data processing unit 40.

<Example of natural sentence database>
Next, the natural sentence database 26 will be described with reference to FIG. FIG. 27 is a diagram illustrating an example of a natural sentence database.

  As shown in FIG. 27, a pattern sentence corresponding to a natural sentence input by a user is set by a pattern (pattern) ID. As shown in FIG. 27, for example, the pattern ID “1” includes “a graph indicating the number of logs by year”, “a bar graph indicating the number of logs by year”, “a graph indicating the number of logs by year”, Four examples of “graphs by number of cases by year” are shown.

  These are combined from the three elements of “number of logs”, “by year”, and “graph”. The order of the combination is different, but the same ID is set because they indicate the same content. ing. As described above, the plurality of pattern sentences are set with the same ID in order to be able to cope with the case where the natural sentence is input in various words and orders by the user.

  Similarly, in the pattern ID “2”, two examples of “a pie chart showing the number of logs by year” and “a pie chart showing the number of logs by year” are shown. Therefore, it can be seen that the pattern ID “2” is combined from the three elements “number of logs”, “by year”, and “pie graph”.

  In addition, the pattern ID “3” shows an example of “line graph showing the number of violations by month”, and is combined from three elements of “number of violations”, “monthly”, and “line graph”. I understand that. The pattern ID “4” shows an example of “a table showing the number of paper output for each MFP”, which is a combination of three elements “paper output number”, “for each MFP”, and “table”. You can see that.

  The above-described three elements shown in FIG. 27 correspond to “main item” and “sub-item” that are analysis items of log information, and “expression format” that is a method of expressing an analysis result. A plurality of sentences that are assumed for log information analysis, in which these three elements are combined, are patterned. A pattern management table 25 shown in FIG. 26 is obtained by dividing each patterned pattern sentence into main items, sub items, and expression formats, and tabulating the divided main items, sub items, and expression formats.

  As described above, according to the present invention, it is possible to analyze log information by inputting a simple natural sentence and visually display a target analysis result.

  The preferred embodiments of the present invention have been described in detail above, but the present invention is not limited to such specific embodiments, and various modifications can be made within the scope of the gist of the present invention described in the claims. Can be changed.

It is a figure which shows the schematic structural example of a log information analysis visual system. A functional configuration of the log information analysis / visualization apparatus will be described. It is a figure which shows the hardware structural example of a log information analysis visualizing apparatus. It is a figure which shows an example of the log information accumulate | stored in an image processing apparatus. It is a figure which shows an example of the target free input screen by a natural sentence. It is a figure which shows an example of a target confirmation screen. It is a figure which shows an example of the analysis result displayed by the designated expression format. It is a figure which shows an example of the target free input screen by a natural sentence. It is a figure which shows an example of a target confirmation screen. It is a figure which shows an example of the analysis result displayed by the designated expression format. It is a figure which shows an example of the target free input screen by a natural sentence. It is a figure which shows an example of a target confirmation screen. It is a figure which shows an example of the analysis result displayed by the designated expression format. It is a sequence flowchart which shows the 1st Example of a log analysis processing procedure. It is a sequence flowchart which shows the 2nd Example of a log analysis processing procedure. It is a flowchart which shows an example of the analysis object range item extraction procedure. It is a flowchart which shows an example of a pattern sentence specific process sequence. It is a flowchart which shows an example of the process sequence according to process ID in a sentence analysis part. It is a flowchart which shows an example of a log information collection process sequence. It is a figure which shows an example of a continuous log set list. It is a flowchart which shows an example of the continuous log extraction process sequence in a log data processing part. It is a figure which shows an example of the analysis object range item. It is a figure which shows an example of the main item which comprises an analysis item. It is a figure which shows an example of the subitem which comprises an analysis item. It is a figure which shows an example of the expression format which displays an analysis result. It is a figure which shows an example of a pattern table. It is a figure which shows an example of a natural sentence database.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Screen control part 11 Request reception part 12 Log display part 20 Sentence analysis part 21 Context analysis part 22 Pattern management part 23 Natural sentence search processing part 24 Synonym dictionary 25 Pattern management table 26 Natural sentence database 30 Sentence learning part 40 Log data processing Unit 41 Log data 51 Input device 52 Output device 53 Drive device 54 Auxiliary storage device 55 Memory device 56 Arithmetic processing device 57 Interface device 58 Storage device 100 Log management / visible server 102 Log information DB
103 Management console 104 PC terminal 105 MFP
106 Copier 107 Scanner Machine

Claims (15)

A log information analysis visual device that analyzes log information accumulated by operation of an image processing device and displays an analysis result,
A pattern sentence specifying means for specifying a pattern sentence configured using at least an analysis item and an expression format for analyzing the log information from the input natural sentence;
Log information collecting means for collecting the log information based on an analysis item included in the pattern sentence specified by the pattern sentence specifying means;
A log information analyzing and visualizing device, comprising: a screen control unit that generates a screen showing an analysis result in an expression format included in the pattern sentence specified by the log information collecting unit.   The log information collecting unit collects log information based on the analysis item and an analysis target range for analyzing the log information extracted from the natural sentence. Log information analysis visual device.   The log information collection unit estimates a plurality of different consecutive image processing functions included in the analysis target range as a series of processes using similar document information accumulated in advance, and collects corresponding log information. The log information analysis visual apparatus according to claim 1 or 2, wherein   The said screen control means collects the relevant information relevant to the said analysis result from the said log information, and produces | generates the screen match | combined with the said expression format, It is characterized by the above-mentioned. Log information analysis visual device.   The screen control means generates the log information analysis confirmation screen that indicates the analysis target range corresponding to the natural sentence, the analysis item, and the expression format, and that can be changed by a user. The log information analysis visual device according to any one of claims 1 to 4. A log information analysis visual method for analyzing log information accumulated by operation of an image processing apparatus and displaying an analysis result,
A pattern sentence specifying procedure for specifying a pattern sentence composed of at least an analysis item and an expression format for analyzing the log information from the input natural sentence;
A log information collection procedure for collecting the log information based on an analysis item included in the pattern sentence identified by the pattern sentence identification procedure;
And a screen control procedure for generating a screen showing an analysis result in an expression format included in the pattern sentence specified by the log information collection procedure.   The log information collecting procedure collects log information based on the analysis item and an analysis target range for analyzing the log information extracted from the natural sentence. Log information analysis visual method.   In the log information collection procedure, a plurality of different consecutive image processing functions included in the analysis target range are estimated as a series of processes using similar document information accumulated in advance, and corresponding log information is collected. The log information analysis visual method according to claim 6 or 7, characterized in that.   9. The screen control procedure according to claim 6, wherein the screen control procedure collects related information related to the analysis result from the log information and generates a screen according to the expression format. Log information analysis visual method.   The screen control procedure shows the analysis target range corresponding to the natural sentence, the analysis item, and the expression format, and generates a log information analysis confirmation screen that can be set and changed by a user. The log information analysis visual method according to any one of claims 6 to 9. A log information analysis visual program for analyzing log information accumulated by operation of an image processing apparatus and displaying an analysis result,
Computer
A pattern sentence specifying means for specifying a pattern sentence configured using at least an analysis item and an expression format for analyzing the log information from the input natural sentence;
Log information collecting means for collecting the log information based on an analysis item included in the pattern sentence specified by the pattern sentence specifying means;
A log information analysis visual program which functions as a screen control means for generating a screen showing an analysis result by an expression format included in a pattern sentence specified by the log information collection means.   The log information collecting unit collects log information based on the analysis item and an analysis target range for analyzing the log information extracted from the natural sentence. Log information analysis visual program.   The log information collection unit estimates a plurality of different consecutive image processing functions included in the analysis target range as a series of processes using similar document information accumulated in advance, and collects corresponding log information. The log information analysis visual program according to claim 11 or 12, characterized in that   14. The screen control unit according to claim 11, wherein the screen control unit collects related information related to the analysis result from the log information and generates a screen according to the expression format. Log information analysis visual program. A computer-readable storage medium storing a log information analysis visual program for analyzing log information accumulated by operation of an image processing apparatus and displaying an analysis result,
Computer
A pattern sentence specifying means for specifying a pattern sentence configured using at least an analysis item and an expression form for analyzing the log information from the input natural sentence;
Log information collecting means for collecting the log information based on an analysis item included in the pattern sentence specified by the pattern sentence specifying means;
A computer-readable storage medium storing a program for functioning as a screen control unit that generates a screen showing an analysis result by an expression format included in a pattern sentence specified by the log information collection unit.

Images