CN111611211A - File import and archive method, electronic device and storage medium - Google Patents

Abstract

The invention relates to intelligent decision-making of artificial intelligence, and provides a file import and archive method, which includes: transmitting files in the form of compressed packages, the compressed packages including one or more files; reading all content items of the transmitted compressed packages, identifying Valid parameters are obtained, the content items include the name of the compressed package, the format of the compressed package, the naming and type of the file in the compressed package, and the source identification of the compressed package, and the valid parameters include file naming or/and file type; The effective parameters of the file name are used to judge whether the file naming conforms to the naming rules; the files that do not conform to the naming rules are imported and the failures and reasons are displayed; the files conforming to the naming rules are filed to the corresponding classification items, and the classification items are classifications according to the file names. Label. The present invention also provides an electronic device and a storage medium. The present invention can automatically archive files. The present invention also relates to blockchain technology, and the compressed package is stored in the blockchain.

Description

File import and archive method, electronic device and storage medium

technical field

The invention relates to the technical field of intelligent decision-making of artificial intelligence, and more particularly, to a file importing and filing method, an electronic device and a storage medium.

Background technique

In the prior art, the file uploading interface usually allows users to transfer the required files to the asset securitization system (Asset-backed Securities, ABS) multiple times one by one. Unnecessary operation time is extended. For the reading of the system, it is also impossible to analyze the archived data in a unified and complete manner, and there may be an omission or incomplete reading of the data transmitted multiple times. Moreover, this will confuse users because they cannot "effectively transfer all at once". For example, Asset-backed Securities (ABS) need to archive user-uploaded materials in different directories, and only one file can be archived at a time To the corresponding directory, when multiple files are archived, the files need to be read and archived repeatedly. There are many repeated and mechanical behavior scenarios during use. In addition, the user cannot know how many files have been uploaded or whether the upload is successful. That is to say, users cannot quickly know the current behavior progress and system feedback. Therefore, the filing of files in the prior art cannot realize the one-time unified filing of multiple files, and cannot show the reason why the files cannot be filed. It requires the help of manual customer service, and the user experience is poor, especially in the filing of R&D documents of complex products. It is easy to cause missing functional iterations, increase the cost of product development, and reduce revenue.

SUMMARY OF THE INVENTION

In view of the above problems, the purpose of the present invention is to provide a file import and filing method, an electronic device and a storage medium capable of automatically filing files.

In order to achieve the above object, the present invention provides an electronic device, the electronic device includes a memory and a processor, the memory stores a file import and archive program, and the file import and archive program is executed by the processor to achieve the following steps :

transmitting the file in the form of a compressed package, the compressed package including one or more files;

Read all the content items of the transmitted compressed package, and identify the valid parameters, the content items include the name of the compressed package, the compressed package format, the naming and type of the files in the compressed package, and the source identifier of the compressed package, and the valid parameters including file naming or/and file type;

Determine whether the file naming conforms to the naming rules according to the identified valid parameters;

Display the failure of importing files that do not meet the naming rules and the reasons;

Files that conform to the naming rules are archived into corresponding classification items, where the classification items are classification labels classified according to file names.

In addition, in order to achieve the above purpose, the present invention also provides a method for importing and filing files, comprising:

transmitting the file in the form of a compressed package, the compressed package including one or more files;

Read all the content items of the transmitted compressed package, and identify the valid parameters, the content items include the name of the compressed package, the compressed package format, the naming and type of the files in the compressed package, and the source identifier of the compressed package, and the valid parameters including file naming or/and file type;

Determine whether the file naming conforms to the naming rules according to the identified valid parameters;

Display the failure of importing files that do not meet the naming rules and the reasons;

Files that conform to the naming rules are archived into corresponding classification items, where the classification items are classification labels classified according to file names.

In one embodiment, the step of displaying import failures and reasons for files that do not meet the naming rules includes: displaying all file names and reasons for import failures in the form of a pop-up window.

Preferably, the pop-up window includes a first pop-up window, a second pop-up window and a third pop-up window. The first pop-up window is used to display the import failure and the reason on the client side that uploads the file, and the second pop-up window is used to display the import failure and the reason to the uploading client. The client of the file provides the option to ignore the error and import the file, and a third popup is used to provide the client with the option of re-uploading.

Further, preferably, the step of displaying the failure of importing and the reasons for the files that do not meet the naming rules also includes: when the number of files that fail to import is less than the set number, a second pop-up window pops up; When the number of files is not less than the set number, a third pop-up window will pop up.

In one embodiment, the compressed package is stored in the blockchain, and the step of filing the files conforming to the naming rules to the corresponding classification items includes:

Extract the keywords of the files in the compressed package according to the naming rules, obtain the eigenvalues of the keywords of the files in the compressed package through the vector space model, and the eigenvalues of all the keywords of each file constitute the file feature vector;

Build a feature vector-based classification model;

The feature vector of the files in the compressed package is input into the classification model to predict the files in the compressed package, and the files in the compressed package are archived to the corresponding classification items.

Preferably, the step of constructing a feature vector-based classification model includes:

According to the number of common keywords, a set number of archived files matching each file are filtered out as the training set of each file;

The feature vector of the archived files of the training set of each file constitutes the feature matrix of the training set, and the classification items of the archived files constitute the classification item matrix of the training set;

Obtain the keyword filing probability that each keyword of the file is filed in each category item through the feature matrix and the classification item matrix of the training set of the file;

Filter out the classification item with the highest keyword archiving probability as the best classification item for the keyword;

According to the best classification item of each keyword of the file and its corresponding keyword archiving probability, the file archiving probability of the file belonging to each classification item is obtained, and a classification model is constructed.

Wherein, the step of filing the files in the compressed package to the corresponding classification item includes:

The classification items are displayed in descending order of the file archiving probability for the client to choose, or the file can be directly archived to the classification item with the highest file archiving probability.

In one embodiment, the content item further includes an authorization identifier of the compressed package or an authorization identifier of each file in the compressed package, where the authorization identifier is a unique identifier of the client.

Further, preferably, the step of constructing the feature vector of the archived files of the training set of each file includes:

The word frequency of each keyword in the archived files of the training set of each file is obtained by the following formula

Among them, TF( _W'm ,d' _n ) is the word frequency of the _mth keyword W'm relative to the archived file d' _n , count( _W'm ,d' _n ) is the keyword _W'm in the archived file d'n. The number of occurrences in the archived file d' _n , count(d' _n ) is the sum of the occurrences of all keywords in the archived file d'_n;

Obtain the inverse word frequency of each keyword of the archived files of the training set of each file by the following formula

Among them, IDF(W' _m ) is the inverse word frequency of the keyword W' _m , d ^m is the archived file where the keyword W' _m appears, and count(d ^m ) is the number of archived files where the keyword W' _m appears. Number, n is the number of archived files in the filtered training set;

The word frequency-inverse word frequency of each keyword of the archived files of the training set of each file is obtained by the following formula, as the feature value of the keyword, and the feature value of each keyword of each archived file constitutes a feature vector

TFIDF( _W'm ,d' _n )＝TF( _W'm ,d' _n )*IDF( _W'm )

Among them, TFIDF( _W'm ,d' _n ) is the word frequency-inverse word frequency of the keyword _W'm in the archived file d' _n .

In addition, in order to achieve the above object, the present invention also provides a computer-readable storage medium, the computer-readable storage medium includes a file importing and archiving program, and when the file importing and archiving program is executed by a processor, the above-mentioned file importing is realized. The steps of the filing method.

The file importing and filing method, electronic device and storage medium of the present invention transmits a single compressed package file in the form of a compressed package, reads out all content items in the transmitted compressed package, identifies effective parameters, and categorizes different types of files. The files are placed into the corresponding classification items at one time, to realize automatic matching and dynamic allocation of files in the compressed package, to display the import failure and the reason of the files that do not meet the naming rules, and to feed back the files that have not been successfully read to the system in a timely manner. On the client side, technologies such as "artificial intelligence matching" are applied to each business scenario, reducing repeated, single and multiple usage scenarios.

Description of drawings

Fig. 1 is the application environment schematic diagram of the preferred embodiment of the file importing and filing method of the present invention;

Fig. 2 is the module schematic diagram of the preferred embodiment of file import filing program among Fig. 1;

FIG. 3 is a flow chart of a preferred embodiment of the file importing and filing method of the present invention.

Detailed ways

It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

The invention provides a file importing and filing method, which is applied to an electronic device. Referring to FIG. 1 , it is a schematic diagram of an application environment of a preferred embodiment of the file importing and archiving method of the present invention.

In this embodiment, the electronic device 1 may be a terminal client with computing functions, such as a server, a mobile phone, a tablet computer, a portable computer, and a desktop computer.

The electronic device 1 includes a memory 11 , a processor 12 , a network interface 13 and a communication bus 14 .

The memory 11 includes at least one type of readable storage medium. The at least one type of readable storage medium may be a non-volatile storage medium such as a flash memory, a hard disk, a multimedia card, a card-type memory, or the like. In some embodiments, the readable storage medium may be an internal storage unit of the electronic device 1 , such as a hard disk of the electronic device 1 . In other embodiments, the readable storage medium may also be an external memory of the electronic device 1, such as a pluggable hard disk, a smart memory card (Smart Media Card, SMC) equipped on the electronic device 1, Secure digital (Secure Digital, SD) card, flash memory card (Flash Card) and so on.

In this embodiment, the readable storage medium of the memory 11 is generally used to store the file import and archive program 10 installed in the electronic device 1 and the like. The memory 11 can also be used to temporarily store data that has been output or is to be output.

The processor 12 may be a central processing unit (Central Processing Unit, CPU), a microprocessor or other data processing chips in some embodiments, and is used to execute program codes or process data stored in the memory 11, such as executing file importing and filing Procedure 10 et al.

The network interface 13 may optionally include a standard wired interface, a wireless interface (such as a WI-FI interface), and is generally used to establish a communication connection between the electronic device 1 and other electronic clients.

The communication bus 14 is used to realize the connection communication between these components.

Figure 1 shows only the electronic device 1 with components 11-14, but it should be understood that implementation of all of the components shown is not a requirement and that more or fewer components may be implemented instead.

Optionally, the electronic device 1 may also include a user interface, and the user interface may include an input unit such as a keyboard (Keyboard), a voice input device such as a microphone (microphone), and a client with a voice recognition function, a voice output device such as a speaker, a headset etc. Optionally, the user interface may also include a standard wired interface and a wireless interface.

Optionally, the electronic device 1 may further include a display, which may also be referred to as a display screen or a display unit.

In some embodiments, it can be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an organic light-emitting diode (Organic Light-Emitting Diode, OLED) touch device, and the like. The display is used for displaying information processed in the electronic device 1 and for displaying a visual user interface.

Optionally, the electronic device 1 further includes a touch sensor. The area provided by the touch sensor for the user to perform a touch operation is called a touch area. In addition, the touch sensor described herein may be a resistive touch sensor, a capacitive touch sensor, or the like. Moreover, the touch sensor includes not only a contact-type touch sensor, but also a proximity-type touch sensor and the like. In addition, the touch sensor may be a single sensor, or may be a plurality of sensors arranged in an array, for example.

Optionally, the electronic device 1 may further include a logic gate circuit, a sensor, an audio circuit, and the like, which will not be repeated here.

In the apparatus embodiment shown in FIG. 1 , the memory 11 as a computer storage medium may include an operating system and a file import and archive program 10; the processor 12 implements the following steps when executing the file import and archive program 10 stored in the memory 11 :

transmitting the file in the form of a compressed package, the compressed package including one or more files;

Read all the content items of the transmitted compressed package, and identify the valid parameters, the content items include the name of the compressed package, the compressed package format, the naming and type of the files in the compressed package, and the source identifier of the compressed package, and the valid parameters including file naming or/and file type;

Determine whether the file naming conforms to the naming rules according to the identified valid parameters;

Display the failure of importing files that do not meet the naming rules and the reasons;

Files that conform to the naming rules are archived into corresponding classification items, where the classification items are classification labels classified according to file names. It should be emphasized that, in order to further ensure the privacy and security of the above compressed package, the above compressed package can also be stored in a node of a blockchain.

In other embodiments, the file importing and archiving program 10 can also be divided into one or more modules, and one or more modules are stored in the memory 11 and executed by the processor 12 to complete the present invention. A module referred to in the present invention refers to a series of computer program instruction segments capable of accomplishing specific functions. Referring to FIG. 2 , it is a functional block diagram of a preferred embodiment of the file import and archive program 10 in FIG. 1 . The file import and archive program 10 can be divided into a transmission module 110, a parameter reading module 120, a judgment module 130, a display module 140 and an archive module 150, wherein:

The transmission module 110, transmits the file in the form of a compressed package, and the compressed package includes one or more files;

The parameter reading module 120 reads all the content items of the transmitted compressed package, and identifies valid parameters, the content items include the name of the compressed package, the compressed package format, the name and type of the files in the compressed package, and the source of the compressed package Identification, the valid parameters include file naming or/and file type;

The judgment module 130 judges whether the file naming conforms to the naming rules according to the identified valid parameters, if it does not conform to the naming rules, sends a signal to the display module 140, and if it conforms to the naming rules, sends a signal to the filing module 150;

The display module 140 displays the import failure and the reason for the files that do not meet the naming rules;

The archiving module 150 archives the files conforming to the naming rules to corresponding classification items, where the classification items are classification labels classified according to the file names.

In an optional embodiment, the above-mentioned display module 140 displays all file names and reasons for import failure in the form of a pop-up window.

Preferably, the display module 140 includes:

a first pop-up window setting unit, which sets a first pop-up window, and the first pop-up window is used to display the import failure and the reason on the client side that uploads the file;

The second pop-up window setting unit is configured to set a second pop-up window, and the second pop-up window is used to provide an option of ignoring errors and importing the file to the client that uploads the file;

The third pop-up window setting unit is configured to set a third pop-up window, and the third pop-up window is used to provide the client with the option of re-uploading.

Further, preferably, the display module 140 further includes:

The pop-up window selection unit, when the number of files that fail to import is less than the set number, sends a signal to the second pop-up window setting unit to pop up the second pop-up window on the client; when the number of files that fail to import is not less than the set number , send a signal to the third pop-up window setting unit, and pop up the third pop-up window on the client side.

In an optional embodiment, the parameter reading module 120 includes:

Read unit, read the name and format of the compressed package;

The storage unit stores the read compressed package in the form of a file;

The format conversion unit converts the stored compressed package into the set compression format;

The loop unit reads the compressed package in the converted format cyclically, and obtains each file in the compressed package.

In one embodiment, the filing module 150 includes:

The feature vector obtaining unit extracts the keywords of each file according to the naming rules, constructs the feature vectors of the keywords of the files in the compressed package through the vector space model, and the feature values of all the keywords of each file constitute the feature of the file. vector;

A model building unit to build a classification model based on feature vectors;

The filing unit predicts the files in the compressed package through the classification model, and archives the files in the compressed package to the corresponding classification item.

Preferably, the model building unit includes:

The training set constructs a subunit, and filters out the set number of archived files that match each file according to the number of common keywords, as the training set of each file;

The matrix construction subunit, the feature vector of the archived files of the training set of each file constitutes the feature matrix of the training set, and the classification items of the archived files constitute the classification item matrix of the training set;

The keyword filing probability obtaining subunit obtains the keyword filing probability that each keyword of the file is filed in each classification item through the feature matrix and the classification item matrix of the training set of the file;

Screening subunits, and screening out the classification item with the highest keyword archiving probability as the best classification item for the keyword;

The file filing probability obtaining subunit obtains the file filing probability that the file belongs to each classification item according to the best classification item of each keyword of the file and its corresponding keyword filing probability, and constructs a classification model,

Among them, the filing unit displays the classification items in the order of file filing probability from high to low, so that the client can choose to file the file to the displayed classification item, or directly file the file to the classification item with the highest file filing probability. .

The above-mentioned electronic devices can provide "real-time visual" interactive behavior feedback, which achieves layer-by-layer cooperation and interlocking from the technical layer to the interface layer to the emotional layer, ensuring that users are given a brand-new full-process interface guidance feedback system to realize technology A good closed-loop experience of ecology and emotional ecology.

In addition, the present invention also provides a file import and archive method. Referring to FIG. 3 , it is a flow chart of a preferred embodiment of file importing and filing according to the present invention. The method may be performed by an apparatus, which may be implemented in software and/or hardware.

In this embodiment, the file import and archive method includes:

Step S1, transmit the file in the form of a compressed package, and the compressed package includes one or more files;

Step S2, read all the content items of the transmitted compressed package, identify valid parameters, and the content items include the name of the compressed package, the compressed package format, the naming and type of the file in the compressed package and the source identifier of the compressed package (such as IP address, etc.), the valid parameters include file name or/and file type;

Step S3, according to the identified valid parameters, determine whether the file naming conforms to the naming rules. For example, the supported formats of the compressed package include zip and 7z, and the compressed package includes one or more doc. or docx. files named according to the naming convention. The naming rules are: Product name + file name + 6-digit year, month and day, such as "A product plan specification 20190101";

In step S4, the files that do not meet the naming rules are displayed as import failures and reasons. Preferably, in the form of a pop-up window, all file names and reasons for import failures are displayed, and the reasons include repeated file naming and irregular file naming. , the file format is not supported, etc.;

In step S5, the files that meet the naming rules are filed into the corresponding classification items, and the classification items are classification labels classified according to the file names. For example, the file naming includes plan specifications, standard terms, trusteeship agreements, etc. After filling in the naming rules, the file can be read successfully and uploaded to the corresponding file type directory (category item) on the page. For another example, the asset securitization system (Asset-backed Securities, ABS) includes project initiation reports, application materials, auditing There are five categories of materials, registration and listing, and the files in the compressed package are archived to the corresponding items in the five categories at one time.

The above-mentioned file import and archiving method in the human-computer interaction behavior, from one by one to a unified single improvement, is not only a leap in the optimization of user efficiency, but also an irreversible improvement in the reform and innovation of the entire technical department. lack of effective productivity.

Preferably, the pop-up window in step S4 includes a first pop-up window, a second pop-up window and a third pop-up window. The first pop-up window displays the import failure and the reason on the client that uploads the file, and the second pop-up window displays the import failure and the reason on the client that uploads the file. The terminal displays "Ignore and submit" for the client to choose, and the third pop-up window displays "Re-upload" on the client for the client to choose. Further preferably, when the number of files that fail to import is less than the set number, The second pop-up window will pop up, and the third pop-up window will pop up when the number of files that fail to import is not less than the set number. In addition, when the client selects the third pop-up window, it will give up the instruction to receive the successfully read file, and the client can modify it offline and then submit it uniformly.

In one embodiment, step S2 includes:

Read the compressed package name and format;

Store the read compressed package in the form of a file;

Convert the stored compressed package to the set compression format;

Read the compressed package in the converted format in a loop, obtain each file in the compressed package, crawl the file name or/and file type of each file, and identify the effective parameters of the compressed package.

In one embodiment, step S5 includes:

Extract the keywords of the files in the compressed package according to the naming rules, obtain the eigenvalues of the keywords of the files in the compressed package through the vector space model, and the eigenvalues of all the keywords of each file constitute the eigenvectors of the file;

Build a feature vector-based classification model;

The feature vector of the files in the compressed package is input into the classification model to predict the files in the compressed package, and the files in the compressed package are archived to the corresponding classification items.

Preferably, the classification model building step includes:

According to the number of common keywords, a set number of archived files matching each file are filtered out as the training set of each file;

The feature vector of the archived files of the training set of each file constitutes the feature matrix of the training set, and the classification items of the archived files constitute the classification term matrix of the training set

C=[c ₁ , c ₂ . . . c _a ]

Among them, F is the feature matrix of the training set of file d _i , C is the classification item matrix of the training set of file d _i , m is the total number of eigenvalues of keywords, n is the set number of filtered archived files, f _nm is the eigenvalue of the keyword W' _m of the archived file d' _n , and C _a is the a-th classification item;

Through the feature matrix and classification item matrix of the training set of the document, the archiving probability of each keyword of the document being archived in each classification item is obtained according to the following formula

Among them, f' _ma is the eigenvalue of the keyword W' _m relative to the classification item C _a , P(W' _m |C _a ) represents the keyword filing probability of the keyword W' _m being filed in the classification item C _a , and the key The word _W'm is _also the key word of the document di;

Filter out the classification item with the highest keyword archiving probability as the best classification item for the keyword;

According to the best classification item of each keyword of the file and its corresponding keyword archiving probability, the file archiving probability of the file belonging to each classification item is obtained

Among them, C _a is the total number of keywords with the classification item C _a as the best classification item, n _a is the total number of keywords filed in the classification item C _a , M is the total number of keywords in the file d _i , and W _j is The jth keyword Pd _i C _a of the file d _i represents the file filing probability that the file d _i is filed to the classification item C _a ;

File files to each category item are displayed in descending order of file filing probability for the client to choose, or directly file files to the category item with the highest file filing probability.

Further, preferably, the step of constructing the feature vector of the archived files of the training set of each file includes:

The word frequency of each keyword in the archived files of the training set of each file is obtained by the following formula;

Among them, TF( _W'm ,d' _n ) is the word frequency of the _mth keyword W'm relative to the archived file d' _n , count( _W'm ,d' _n ) is the keyword _W'm in the archived file d'n. The number of occurrences in the archived file d' _n , count(d' _n ) is the sum of the occurrences of all keywords in the archived file d'_n;

The inverse word frequency of each keyword in the archived files of the training set of each file is obtained by the following formula;

Among them, IDF(W' _m ) is the inverse word frequency of the keyword W' _m , d ^m is the archived file where the keyword W' _m appears, and count(d ^m ) is the number of archived files where the keyword W' _m appears. quantity;

The word frequency-inverse word frequency of each keyword of the archived files of the training set of each file is obtained by the following formula, as the feature value of the keyword, and the feature value of each keyword of each archived file constitutes a feature vector

TFIDF( _W'm ,d' _n )＝TF( _W'm ,d' _n )*IDF( _W'm )

Among them, TFIDF( _W'm ,d' _n ) is the word frequency-inverse word frequency of the keyword _W'm in the archived file d' _n .

In addition, preferably, it also includes:

Divide the correct historical archive file data, and use a part as the training set of the classification model to train the model parameters, and part as the test set of the performance testing department of the classification model;

The performance of the classification model is evaluated and judged through the test set, specifically:

The accuracy rate P of the classification model file filing is evaluated according to the following formula,

The recall rate R of the classification model file filing is evaluated according to the following formula,

Evaluate the F-parameters of the classification model file according to

where β is a trade-off factor between precision P and recall R.

In an optional embodiment, each file in the compressed package may not be archived, but the compressed package may be directly archived, that is to say, the keywords in the compressed package are filtered out according to the number of occurrences to a set number of keywords. The number of common keywords filters out a set number of archived files matching the compressed package as the training set of the compressed package, and the classification items of the compressed package archive are obtained according to the steps in the previous embodiment.

In an optional example, the content item of the compressed package further includes an authorization identifier of the compressed package or an authorization identifier of each file in the compressed package, where the authorization identifier is the unique identifier of the client, for example, the employee number or identity of the employee. The certificate number, etc., is used as the authorization identifier. When the client queries the archived file, the file with the client authorization identifier will be displayed to the client.

In addition, an embodiment of the present invention also provides a computer-readable storage medium, where the computer-readable storage medium includes a file importing and archiving program, and when the file importing and archiving program is executed by a processor, the following steps are implemented:

transmitting the file in the form of a compressed package, the compressed package including one or more files;

Read all the content items of the transmitted compressed package, and identify the valid parameters, the content items include the name of the compressed package, the compressed package format, the naming and type of the files in the compressed package, and the source identifier of the compressed package, and the valid parameters including file naming or/and file type;

Determine whether the file naming conforms to the naming rules according to the identified valid parameters;

Display the failure of importing files that do not meet the naming rules and the reasons;

Files that conform to the naming rules are archived into corresponding classification items, where the classification items are classification labels classified according to file names. It should be emphasized that, in order to further ensure the privacy and security of the above compressed package, the above compressed package can also be stored in a node of a blockchain.

The specific implementations of the computer-readable storage medium of the present invention are substantially the same as the specific implementations of the above-mentioned file importing and archiving method and electronic device, and will not be repeated here.

The blockchain referred to in the present invention is a new application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, and encryption algorithm. Blockchain, essentially a decentralized database, is a series of data blocks associated with cryptographic methods. Each data block contains a batch of network transaction information to verify its Validity of information (anti-counterfeiting) and generation of the next block. The blockchain can include the underlying platform of the blockchain, the platform product service layer, and the application service layer.

It should be noted that, herein, the terms "comprising", "comprising" or any other variation thereof are intended to encompass non-exclusive inclusion, such that a process, device, article or method comprising a series of elements includes not only those elements, It also includes other elements not expressly listed or inherent to such a process, apparatus, article or method. Without further limitation, an element qualified by the phrase "comprising a..." does not preclude the presence of additional identical elements in the process, apparatus, article, or method that includes the element.

The above-mentioned serial numbers of the embodiments of the present invention are only for description, and do not represent the advantages or disadvantages of the embodiments. From the description of the above embodiments, those skilled in the art can clearly understand that the method of the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is better implementation. Based on such understanding, the technical solutions of the present invention can be embodied in the form of software products in essence or the parts that make contributions to the prior art, and the computer software products are stored in a storage medium (such as ROM/RAM) as described above. , disk, optical disk), including several instructions to make a terminal client (which may be a mobile phone, computer, server, or network client, etc.) execute the methods described in the various embodiments of the present invention.

The above are only preferred embodiments of the present invention, and are not intended to limit the scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the description and drawings of the present invention, or directly or indirectly applied in other related technical fields , are similarly included in the scope of patent protection of the present invention.

Claims (10)

1. a file import filing method, is characterized in that, comprises: transmitting the file in the form of a compressed package, the compressed package including one or more files; Read all the content items of the transmitted compressed package, and identify the valid parameters, the content items include the name of the compressed package, the compressed package format, the naming and type of the files in the compressed package, and the source identifier of the compressed package, and the valid parameters including file naming or/and file type; Determine whether the file naming conforms to the naming rules according to the identified valid parameters; Display the failure of importing files that do not meet the naming rules and the reasons; Files that conform to the naming rules are archived into corresponding classification items, where the classification items are classification labels classified according to file names. 2. the file import filing method according to claim 1, is characterized in that, the described step that the file that does not meet the naming rule to carry out import failure and the display of reason comprises: in the form of a pop-up window, showing all the import failures File name and reason. 3. The file importing and archiving method according to claim 2, wherein the pop-up window comprises a first pop-up window, a second pop-up window and a third pop-up window, and the first pop-up window is used for uploading files on a client side Displays the import failure and the reason, the second pop-up window is used to provide the client uploading the file with the option to ignore the error and import the file, and the third pop-up window is used to provide the client with the option of re-uploading. 4. the file import filing method according to claim 3, is characterized in that, the described step that the file that does not meet naming rule is carried out import failure and the display of reason also comprises: when the file of import failure is less than the set number , the second pop-up window will pop up; when the number of files that fail to import is not less than the set number, the third pop-up window will pop up. 5. The file import filing method according to claim 1, wherein the compressed package is stored in the block chain, and the step of filing the files that meet the naming rules to the corresponding classification items comprises: Extract the keywords of the files in the compressed package according to the naming rules, obtain the eigenvalues of the keywords of the files in the compressed package through the vector space model, and the eigenvalues of all the keywords of each file constitute the eigenvectors of the file; Build a feature vector-based classification model; The feature vector of the files in the compressed package is input into the classification model to predict the files in the compressed package, and the files in the compressed package are archived to the corresponding classification items. 6. The file import filing method according to claim 5, wherein the step of constructing a feature vector-based classification model comprises: According to the number of common keywords, a set number of archived files matching each file are filtered out as the training set of each file; The feature vector of the archived files of the training set of each file constitutes the feature matrix of the training set, and the classification items of the archived files constitute the classification item matrix of the training set; Obtain the keyword filing probability that each keyword of the file is filed in each category item through the feature matrix and the classification item matrix of the training set of the file; Filter out the classification item with the highest keyword archiving probability as the best classification item for the keyword; According to the best classification item of each keyword of the file and its corresponding keyword archiving probability, the file archiving probability of the file belonging to each classification item is obtained, and a classification model is constructed. Wherein, the step of filing the files in the compressed package to the corresponding classification item includes: The classification items are displayed in descending order of the file archiving probability for the client to choose, or the file can be directly archived to the classification item with the highest file archiving probability. 7. The file import filing method according to claim 6, wherein the step of constructing the feature vector of the archived file of the training set of each file comprises: The word frequency of each keyword in the archived files of the training set of each file is obtained by the following formula

Among them, TF(W′ _m , d′ _n ) is the word frequency of the mth keyword W′ _m relative to the archived file d′ _n , and count(W′ _m , d′ _n ) is the word frequency of the keyword W′ _m in the archived file d′ n . The number of occurrences in the archived file d' _n , count(d' _n ) is the sum of the number of occurrences of all keywords in the archived file d'_n; Obtain the inverse word frequency of each keyword of the archived files of the training set of each file by the following formula

Among them, IDF(W' _m ) is the inverse word frequency of the keyword W' _m , d ^m is the archived file where the keyword W' _m appears, and count(d ^m ) is the number of archived files where the keyword W' _m appears. Number, n is the number of archived files in the filtered training set; The word frequency-inverse word frequency of each keyword of the archived files of the training set of each file is obtained by the following formula, as the feature value of the keyword, and the feature value of each keyword of each archived file constitutes a feature vector TFIDF(W' _m , d' _n )=TF(W' _m , d' _n )*IDF(W' _m ) Among them, TFIDF(W' _m , d' _n ) is the word frequency-inverse word frequency of the keyword W' _m in the archived file d' _n . 8 . The file importing and archiving method according to claim 1 , wherein the content item further comprises an authorization identifier of the compressed package or an authorization identifier of each file in the compressed package, and the authorization identifier is a unique identifier of the client. 9 . 9. An electronic device, comprising a memory and a processor, wherein a file import filing program is stored in the memory, and when the file import filing program is executed by the processor, the following steps are implemented: transmitting the file in the form of a compressed package, the compressed package including one or more files; Read all the content items of the transmitted compressed package, and identify the valid parameters, the content items include the name of the compressed package, the compressed package format, the naming and type of the files in the compressed package, and the source identifier of the compressed package, and the valid parameters including file naming or/and file type; Determine whether the file naming conforms to the naming rules according to the identified valid parameters; Display the failure of importing files that do not meet the naming rules and the reasons; Files that conform to the naming rules are archived into corresponding classification items, where the classification items are classification labels classified according to file names. 10. A computer-readable storage medium, characterized in that, the computer-readable storage medium includes a file import and archive program, and when the file import archive program is executed by the processor, the implementation of any one of claims 1 to 8 is realized. 1. The steps of a method for importing a file as claimed in claim.

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