CN117149951A - An intelligent retrieval method, device, electronic equipment and storage medium - Google Patents

Abstract

The application discloses an intelligent retrieval method, a system, electronic equipment and a storage medium, which are characterized in that text identifiers in a document library corresponding to text input by a user in a pre-established inverted index list are read according to the text input by the user, and the text identifiers in the document library corresponding to the text input by the user read from the inverted index list are stored in a two-dimensional array, so that the matching degree of the text corresponding to the text identifiers in the document library stored in the two-dimensional array is calculated only during retrieval, and the matching degree of all the texts in the document library is not calculated, thereby greatly improving the retrieval efficiency.

Description

An intelligent retrieval method, device, electronic equipment and storage medium

Technical field

This application relates to the field of data processing technology, and in particular to an intelligent retrieval method, device, electronic equipment and storage medium.

Background technique

With the development of intelligent retrieval technology, more and more retrieval systems have appeared in the public eye. Especially when used in the public security system, the search for laws, regulations, cases and related scenarios is of great help to improve the efficiency of police case handling.

However, for searches of laws, regulations, cases, and related scenarios, traditional retrieval methods obtain the text input by the user, and then compare the text entered by the user with all the texts saved in the retrieval database word by word until the relevant text is retrieved. The search results will be output only if the text input by the user matches the text, which leads to a lot of time wasted on retrieval during the case handling process and reduces the efficiency of the police case handling.

Contents of the invention

In view of the above problems, this application provides an intelligent retrieval method, device, electronic equipment and storage medium to implement. The specific plans are as follows:

An intelligent retrieval method including:

Get the text entered by the user;

Based on the text entered by the user, read the text identifier in the document library corresponding to the text entered by the user in the pre-established inverted index list, and read the document corresponding to the text entered by the user from the inverted index list Text identifiers in the library are stored in a two-dimensional array;

Calculate the matching degree between the text corresponding to the text identifier in the document library stored in the two-dimensional array and the text input by the user one by one;

Determine the text whose matching degree meets the preset requirements, use it as a search result corresponding to the text input by the user, and output it.

Optionally, the process of pre-building the inverted index list includes:

Extract the key information of each text in the document library. The key information includes: keywords or keywords;

Generate an inverted index list corresponding to each text in the document library. The inverted index list contains key information and contains text identifiers corresponding to the key information.

Optionally, storing the text identifier in the document library corresponding to the user-entered text read from the inverted index list in a two-dimensional array includes:

The text in the document library read from the inverted index is stored in the row information of the two-dimensional array. Each row of information in the two-dimensional array represents each text information in the document library;

The length information of the text in the document library read from the inverted index is stored in the column information of the two-dimensional array. Each column information in the two-dimensional array represents the length information of each text in the document library.

Optionally, calculating the matching degree between the text corresponding to the text identifier in the document library stored in the two-dimensional array and the text input by the user one by one includes:

Calculate the maximum common string length of the text entered by the user and the text identifier stored in the document library stored in the two-dimensional array respectively. The maximum common string length is the text entered by the user and the text identifier stored in the document library stored in the two-dimensional array. The same and continuous field length between the texts corresponding to the text identifier;

Using the maximum common substring length, the text length input by the user and the text length corresponding to the text identifier in the document library stored in the two-dimensional array, it is calculated that the text input by the user corresponds to the text identifier in the document library stored in the two-dimensional array The matching degree of the text.

Optionally, use the maximum common substring length and the text length input by the user and the text length corresponding to the text identifier in the document library stored in the two-dimensional array to calculate the corresponding text identifier in the document library stored in the two-dimensional array. Matching of text to user-entered text includes:

The matching degree is calculated through the formula for calculating the matching degree. The formula for calculating the matching degree is:

Among them, length(lcs) is the maximum common substring length, length(a) is the text length input by the user, and length(b) is the text length corresponding to the text identifier in the document library stored in the two-dimensional array.

Optionally, determining text whose matching degree meets preset requirements includes:

Determine the matching degree of the text corresponding to the text identifier in the document library stored in all two-dimensional arrays and the text input by the user, and use the text with the highest matching degree as the determined text whose matching degree meets the preset requirements.

Optionally, determining text whose matching degree meets preset requirements includes:

Determine whether the matching degree corresponding to the text with the highest matching degree exceeds the set threshold;

Among them, if it is determined that the matching degree corresponding to the text with the highest matching degree exceeds the set threshold, then the text with the highest matching degree will be regarded as the text whose matching degree is determined to meet the preset requirements;

If it is determined that the matching degree corresponding to the text with the highest matching degree does not exceed the set threshold, then this retrieval will fail.

Optionally, also includes:

Obtain the document name list information corresponding to the text in the document library read from the inverted index, and obtain the last one in each row of the two-dimensional array corresponding to the text in the document library read from the inverted index The positional relationship corresponding to the text that matches the text entered by the user, and stores the information and positional relationship in a two-dimensional array.

An intelligent retrieval system including:

Get module, used to get the text input by the user;

The reading module is used to read the text identifier in the document library corresponding to the text input by the user in the pre-established inverted index list based on the text input by the user, and read out the text from the inverted index list that is consistent with the user input. The text identifier in the document library corresponding to the input text is stored in a two-dimensional array;

The calculation module is used to calculate the matching degree between the text corresponding to the text identifier in the document library stored in the two-dimensional array and the text input by the user one by one;

The output module is used to determine the text whose matching degree meets the preset requirements, as the retrieval result corresponding to the text input by the user, and output it.

An electronic device including at least one processor and a memory connected to the processor, wherein:

Memory is used to store computer programs;

The processor is used to execute computer programs so that the electronic device can implement the aforementioned intelligent retrieval method.

A computer storage medium carries one or more computer programs. When one or more computer programs are executed by an electronic device, the electronic device can implement the aforementioned intelligent retrieval method.

Through the above technical solution, in the intelligent retrieval method provided by this application, because this application reads the text identifier in the document library corresponding to the text input by the user in the pre-established inverted index list based on the text input by the user, And the text identifier in the document library corresponding to the user-entered text read from the inverted index list is stored in a two-dimensional array. Therefore, only the text in the document library stored in the two-dimensional array needs to be retrieved. The matching degree is calculated for the text corresponding to the logo, without the need to calculate the matching degree for all the texts in the document library, thus greatly improving the retrieval efficiency.

Description of the drawings

The above and other features, advantages and aspects of various embodiments of the present application will become more apparent with reference to the following detailed description taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It is to be understood that the drawings are schematic and that elements and elements are not necessarily drawn to scale.

Figure 1 is a flow chart of an intelligent retrieval method provided by this application;

Figure 2 is a schematic interface diagram of an intelligent retrieval system provided by this application;

Figure 3 is a schematic interface diagram of scene search in an intelligent retrieval system provided by this application;

Figure 4 is a schematic structural diagram of an intelligent retrieval device provided by this application;

Figure 5 is a schematic structural diagram of an electronic device provided by this application.

Detailed ways

Embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather these embodiments are provided for Understand this application more thoroughly and completely. It should be understood that the drawings and embodiments of the present application are for illustrative purposes only and are not intended to limit the scope of protection of the present application.

As used herein, the term "include" and its variations are open-ended, ie, "including but not limited to." The term "based on" means "based at least in part on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "At least some embodiments". Relevant definitions of other terms will be given in the description below.

It should be noted that concepts such as “first” and “second” mentioned in this application are only used to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units. Or interdependence.

It should be noted that the modifications of "one" and "multiple" mentioned in this application are illustrative and not restrictive. Those skilled in the art will understand that unless the context clearly indicates otherwise, it should be understood as "one or Multiple”.

In the existing technology, for the search of laws, regulations, cases and related scenarios, the traditional retrieval method is to obtain the text input by the user, and then compare the text input by the user with all the texts saved in the retrieval database, word by word, until The search results will only be output after retrieving text that matches the text entered by the user, which causes the police to waste a lot of time on retrieval during the case handling process and reduces the efficiency of the police case handling.

In order to solve the above problems, the present application provides an intelligent retrieval method, device, electronic device and storage medium. The present application will be introduced in detail below with reference to specific embodiments.

Figure 1 shows a flow chart of an intelligent retrieval method provided by an embodiment of the present application. Specifically, it includes the following steps:

S10. Get the text input by the user.

Figure 2 shows a schematic diagram of an intelligent retrieval system interface provided by an embodiment of the present application. Users can select search categories by clicking on the menu bar, where search categories include regulation search 202, case search 203, and scenario search 204. Each column corresponds to a different search scenario. In Regulation Search 202, you can search for various laws and regulations that deal with different complex case handling scenarios. In Case Search 203, you can search for cases similar to the case being handled by the police handling the case. For reference, scene search 204 can search for scenes similar to the case being handled by the police handling the case for reference.

For example, the user can search for relevant laws and regulations by clicking the regulation search 202 in the menu bar and inputting keywords of relevant laws and regulations in the input field 201.

The laws and regulations library in the intelligent retrieval system provided by the embodiment of this application covers national laws and regulations, local laws and regulations, international treaties and international practices, judicial interpretations, etc., and the content involves various fields in social life. The intelligent retrieval system provided by the embodiment of this application can search for relevant legal provisions from a massive database of laws and regulations through the keywords input by the user. At the same time, the user can also click on the search results to view two to three cases related to the legal provisions. , improve users’ search efficiency.

Similarly, the user can search for related cases by clicking case search 203 in the menu bar and entering the keywords of the related cases in the input field 201. Specifically, the case database in the intelligent retrieval system provided by the embodiment of this application covers common case types in various business departments of the public security police and police stations. Users can search from the massive case database by inputting keywords of relevant cases. Output related cases to the case entered by the user.

It should be noted that the intelligent retrieval system provided by the embodiment of the present application also supports users to search for related scenes. The user can click scene search 204 in the menu bar and enter a simple description of the case scene in the input field 201. The number of words describing the case scenario should be controlled within 500 words to enable searching for relevant case scenarios.

Specifically, users can obtain three parts of search results by searching for case scenarios. The first part mainly includes relevant laws and regulations applicable to the case scenarios that users search. Users can choose from the relevant laws and regulations provided by the intelligent retrieval system to match the user's search results. The most relevant laws and regulations for the scenarios encountered are for users’ reference; the second part mainly includes providing users with two to three case contents related to scenarios similar to the scenarios encountered by users. Users can choose from the two cases provided by the intelligent retrieval system. Go to the three case contents to find content related to the scenarios encountered by users for users to make choices and judgments; the third part mainly includes some standardized law enforcement tips applicable to the scenarios encountered by users. Users can follow the information provided by the intelligent retrieval system. Standardization of law enforcement prompts the adoption of corresponding countermeasures.

For example, FIG. 3 is a schematic interface diagram of scene search in an intelligent retrieval system provided by this application. The user can click scene search 204 in the menu bar and enter a simple description of the case scene in the input field 201. The number of words of the description of the case scene should be controlled within 500 words, thereby realizing the scene search of the relevant case. Search and enter the interface diagram of scene search in the intelligent retrieval system as shown in Figure 3.

As shown in Figure 3, the scene search interface in the intelligent retrieval system includes a search box 301, similar cases 302, an information prompt box 303, and applicable laws and regulations 304. Among them, the search box 301 can be used by the user to continue searching for scene descriptions about related cases. The user can describe the case scene in detail by re-entering descriptors that describe the related case scene in detail. The intelligent retrieval system searches based on the detailed case scene information input by the user. Related case scenarios. Similar cases 302 are used to display brief descriptions of case scenarios related to the user's search. The user can view detailed displays of related cases by clicking on the search results interface to view specific cases. The information prompt box 303 is used to prompt the police handling the case with some solutions to the relevant cases. For example, the police handling the case can click to view the first aid measures and related practices for various injuries. Applicable laws and regulations 304 is used to display to the user the laws and regulations related to the case scenario that the user searches for, so that the user can reasonably and legally handle the relevant cases in accordance with the laws and regulations. At the same time, the user can click to view the search result interface of the specific laws and regulations.

It should also be noted that the intelligent retrieval system provided by the embodiments of this application also supports users to enter cases or law enforcement standardized prompt information by themselves. Specifically, the user can enter the user's resource library interface by clicking My Resource Library 205 in the intelligent retrieval system interface. Specifically, in the user's resource library interface, users can view self-entered case information or law enforcement standardization prompt information. The information entered by users into the resource library can be set to be visible only to themselves. Users with advanced permissions can also enter relevant cases or law enforcement standardization prompt information by themselves. Customers who also have advanced permissions can select the range to be visible, and select only themselves. It is up to the user to choose whether it is visible or visible to everyone.

In addition, the intelligent retrieval system provided by the embodiment of the present application also supports the function of synchronizing the user's personal information data. The user can log in to the same account in different terminal devices, and the personal information between different devices supports the function of data synchronization. It also supports Users can collect commonly used laws, regulations, cases and other functions. It also supports the note-taking function, that is, users can view the case information entered by the user through the note-taking function.

S20. According to the text input by the user, read the text identifier in the document library corresponding to the text input by the user in the pre-established inverted index list, and store the text identifier in the document library read from the inverted index in in a two-dimensional array.

When the intelligent retrieval system provided by the embodiment of the present application searches for text input by the user, it needs to read the text identifier in the document library corresponding to the text input by the user in the pre-established inverted index list. , and store the text identifiers in the document library read from the inverted index list in a two-dimensional array.

It should be noted that the core of the intelligent retrieval system provided by the embodiment of the present application is to use the inverted index to process all texts in the document library. Specifically, the inverted index is a data structure used for full-text search. Split each text in the document library into keywords or key words, and form a list of all documents containing the keyword or keywords, and use this list to replace all texts in the document library.

Specifically, the data structure of an inverted index usually consists of two parts: the dictionary and the inverted list. Among them, what is stored in the dictionary are all keywords or keywords that split the text in the document library into Or the keyword corresponds to the document list in the inverted list. The inverted list is the core data structure of the inverted index. It is used to record which document in the document library each keyword or keyword appears in, and record relevant statistical data, such as the frequency of occurrence in the document, Information such as location information and word frequency in the document.

It should also be noted that the intelligent retrieval system provided by the embodiment of the present application will read the text identifier in the document library corresponding to the user-entered text in the inverted list based on the text input by the user, and will read the text identifier from the inverted list. The text identifiers in the retrieved document library are stored in a two-dimensional array. Specifically, the intelligent retrieval system provided by the embodiment of this application will create a two-dimensional array X*Y, where X represents the number of rows of the two-dimensional array, Y represents the number of columns of the two-dimensional array, and the row information of the two-dimensional array Used to store the document list corresponding to the text in the document library read from the inverted list, that is, the number of document lists corresponding to the text in the document library read from the inverted list and the number of rows of the two-dimensional array Equal, the column information of this two-dimensional array is used to store the document position information stored in the inverted index of the text in the document library read from the inverted list.

S30. Calculate the matching degree between the text corresponding to the text identifier in the document library stored in the two-dimensional array and the text input by the user one by one.

In the embodiment of the present application, it is necessary to calculate the matching degree between the text corresponding to the text identifier in the document library stored in the two-dimensional array and the text input by the user one by one.

It should be noted that when the intelligent retrieval system provided by the embodiment of the present application calculates the matching degree between the text input by the user and the text in the document library, it only needs to calculate the text in the document library stored in the two-dimensional array, and does not need to All text in the document library is calculated to match the text entered by the user, thus greatly improving retrieval efficiency. Specifically, the specific calculation formula for calculating the matching degree between the text input by the user and the text in the document library is:

In the formula, length is used to represent the length of text, length(a) represents the length of text a, length(b) represents the length of text b, and length(lcs) represents the maximum common substring length of text a and text b. In the intelligent retrieval system provided by the embodiment of the present application, length(a) may correspond to the length of the text input by the user, length(b) may correspond to the length of the text in the document library, and length(lcs) may represent the difference between the text input by the user and the document library. The maximum common substring length corresponding to the text in

It should be noted that lcs here refers to the maximum common substring length. The maximum common substring length is different from the longest common subsequence. The longest common subsequence does not require the text in the subsequence to be continuous, while the maximum common substring length The length requires that the text in the substring be continuous.

For example, the largest common subsequence of the string "ascde" and the string "axcxdde" is "de", because "de" is continuous in both strings, and the longest common subsequence is "acde" , because the longest common subsequence does not require the characters in the string to be consecutive, as long as the longest common subsequence is in the same order in the two strings. Therefore, if the matching degree of the string "ascde" and the string "axcxdde" is calculated, the matching degree of the string "ascde" and the string "axcxdde" can be found to be 0.11 through the above formula for calculating the matching degree.

The intelligent retrieval system provided by the embodiment of the present application calculates the matching degree between the text input by the user and the text in the document library stored in the two-dimensional array, and obtains the text in the document library that has the highest matching degree with the text input by the user.

It should be noted that in the intelligent retrieval system provided by the embodiment of the present application, when the inverted index processes the text in the document library, the text in the document library is split into the form of keywords, and the documents containing the keywords are Form a list to form an inverted list. Therefore, when processing the text input by the user, the intelligent retrieval system provided by the embodiment of the present application splits the text input by the user into the form of keywords to match the text input by the user with the text in the document library.

For example, the text entered by the user is "No Fight", and by analyzing the text entered by the user, the document name "Fight Fight" containing the text entered by the user can be queried from the inverted index 250 and the document name for "fight" of 888, and store "fight" with the document name of 250 and "brawl" with the document name of 888 in a two-dimensional array.

Specifically, for the user-entered text "无fight", the text input by the user can be split into the form of keywords, that is, into the form of "无", "fight", and "fight", or the user-entered text can be split into the form of keywords. The input text is split into the form of keyword plus keyword, that is, it is split into the form of "none" and "fight". When calculating the matching degree, the intelligent retrieval system provided by the embodiment of the present application splits the text input by the user into the form of keyword plus keyword, that is, into the form of "none" and "fight".

First, the intelligent retrieval system will process the word "None" in "No Fight". Judging from the document names stored in the inverted index, the inverted index only stores the document name 250 "Fight Fight" and the document name 888 "Fight", the word "无" does not appear in any document name, so the matching degree between the word "None" in "No Fight" and the text in the document library stored in the two-dimensional array is not calculated. The two-dimensional array The data in will not be modified in any way.

Secondly, the intelligent retrieval system will process the keyword "fight" in "no fight". Judging from the document names stored in the inverted index, the document name in the inverted index is "fight" with the name 250 and the document name 888. "Fighting" both hit the keyword "fighting" in the text entered by the user, so it is necessary to calculate the keyword "fighting" in the text entered by the user and the document name "fighting" with the name of 250 in the inverted index and the document name The matching degree of "brawl" for 888.

Specifically, when processing the keyword "fight" in the "no fight" of the text entered by the user, it is necessary to calculate the keyword "fight" in the "no fight" of the text entered by the user and the document name in the inverted index To achieve a matching degree of "fighting" of 250, we first need to determine the maximum common substring length of "no fighting" in the text entered by the user and the document name "fighting" in the inverted index of 250. According to the definition of the maximum common substring length, it can be seen that the maximum common substring length requires the text in the substring to be continuous. Therefore, it can be determined that the "no fight" of the text entered by the user and the "fight" of the document name 250 in the inverted index can be determined The maximum common substring length is 2, that is, length(lcs) can be equal to 2. Next, you need to determine the respective text lengths of "no fighting" of the text entered by the user and "fighting" with a document name of 250 in the inverted index , it can be seen that the text length of "no fighting" of the text entered by the user is 3, and the text length of "fighting" of the document name 250 in the inverted index is 4, so length(a) can be equal to 3, length(b) It can be equal to 4. Substituting the above value into the formula for calculating the matching degree between the text entered by the user and the text in the document library, we can get the "no fight" of the text entered by the user and the "fight" of the document name 250 in the inverted index. "The matching degree is 0.33.

Since there are two documents matching the text entered by the user stored in the inverted index, it is also necessary to calculate the match between the keyword "fight" in "no fight" of the text entered by the user and the document name "fight" of 888 Degree, in the same way, firstly, it is necessary to determine that the maximum common substring length of "no fighting" of the text entered by the user and "fighting" of the document name 888 in the inverted index is 2, that is, length(lcs) can be equal to 2, and secondly Determine the text length of "no brawl" for the text entered by the user is 3, and the text length of "brawl" for the document name 888 in the inverted index is 2, so length(a) can be equal to 3 and length(b) can be equal to 2. Substituting the above values into the formula for calculating the matching degree between the text entered by the user and the text in the document library, we can get the match between "no fighting" of the text entered by the user and "fighting" of the document name 888 in the inverted index. The degree is 0.67.

S40. Determine the text whose matching degree meets the preset requirements, use it as a search result corresponding to the text input by the user, and output it.

In the embodiment of the present application, after the above-mentioned step S30 calculates the matching degree between the text in the document library stored in the two-dimensional array and the text input by the user, the calculated matching degree between the text in the document library and the text input by the user can be calculated. The values are sorted from high to low, and the text corresponding to the highest matching degree is output.

For example, in the above step S30, the matching degree of "no fighting" of the text input by the user and the "fighting and fighting" document name 250 in the inverted index can be obtained by calculation, and the matching degree of "no fighting" of the text entered by the user is 0.33. "The matching degree with the document name 888 in the inverted index is 0.67. Therefore, through comparison, it can be concluded that the highest matching degree with the user-entered text "No Fighting" is the document name 888 in the inverted index. "Fighting", so the document name in the output inverted index is the text corresponding to "Fighting" of 888.

In some other embodiments, a threshold range can also be set before outputting the text with the highest matching degree. Only when the matching degree corresponding to the text with the highest matching degree exceeds the preset threshold range, the text with the highest matching degree will be output. Otherwise, the text with the highest matching degree will be output. The search results will remind the user that the text in the document library does not match the text entered by the user, or the matching degree between the text in the document library and the text entered by the user does not reach the preset threshold range, so the user needs to be reminded to try again. Change keywords or keywords to search.

For example, the embodiment of the present application can set the preset threshold range so that only text with a matching degree greater than 0.8 will be output. Otherwise, the user will be reminded that the search is invalid and the user will be reminded to replace the keyword or keywords. Re-search until the text entered by the user can search for text that meets the threshold range. Specifically, in the above step S30, it can be obtained through calculation that the matching degree of "no fighting" of the text input by the user and the "fighting and fighting" of the document name 250 in the inverted index is 0.33 and the "no fighting" of the text input by the user "The matching degree with "Fight" with the document name 888 in the inverted index is 0.67. Therefore, the calculated matching degrees of the two document names hit by the inverted index do not reach the threshold range preset by the user. Therefore, this time If the search result fails, the user needs to be reminded to search again by changing the keyword or keywords until the text entered by the user can search for text that meets the threshold range.

The embodiment of the present application reads the text in the document library corresponding to the user-input text in the inverted index based on the text input by the user, and stores the text in the document library read from the inverted index in a two-dimensional Therefore, during retrieval, only the text stored in the two-dimensional array needs to be calculated for the matching degree, and there is no need to calculate the matching degree for all texts in the document library, thus greatly improving the retrieval efficiency.

It should be noted that since the intelligent retrieval method provided by the embodiment of the present application needs to traverse the entire two-dimensional array during the retrieval process, and the method of traversing the two-dimensional array is complex and changeable, in order to improve the intelligent retrieval method provided by the embodiment of the present application In order to improve the accuracy and speed of the system, in some embodiments, the intelligent retrieval algorithm provided by this application is also optimized. The specific methods are as follows:

In this embodiment of the present application, when traversing the matching degree between the text in the document library stored in the two-dimensional array and the text input by the user, in order to speed up the process of traversing the two-dimensional array, two additional columns of information can be added to the two-dimensional array for storage. Additional information about the text in the document library.

For example, two additional columns of information are added to the two-dimensional array. One column of information is used to save a list of document names corresponding to the texts in all document libraries read from the inverted index. By adding the document library The list of document names corresponding to the text in is stored in a two-dimensional array. In this way, the retrieval system does not need to traverse all rows and all columns in the two-dimensional array when traversing the two-dimensional array. It only needs to traverse and save and read from the inverted index. The column information corresponding to the list composed of the document names corresponding to the texts in all the document libraries can be retrieved, which greatly saves retrieval time. At the same time, another column of information is added to save the position relationship between the text in the document library read from the inverted index and the last text in each row in the two-dimensional array that matches the text entered by the user. In this way, when the retrieval system traverses the two-dimensional array, it does not need to traverse all the text information stored in all the row information in the two-dimensional array. It only needs to retrieve the last text in each row in the two-dimensional array that matches the text entered by the user. The corresponding position relationship no longer requires traversing the text information stored after each line, which greatly saves retrieval time.

It should be pointed out that the database used in the intelligent retrieval system provided by the embodiment of the present application is a distributed relational database. Distributed relational databases are different from traditional databases. Traditional single-server databases can only expand vertically in terms of processing capabilities. In terms of data volume, When it grows to a certain level, a traditional single server often cannot meet the demand. The advantage of a distributed relational database is that it is easy to expand, and after the distributed relational database is initially created, a new data type can be added without modifying all existing application software. In a distributed relational database, an application can perform transparent operations on the database. The data in the database are stored in different local databases, managed by different database management systems, run on different machines, and supported by different operating systems. , are connected together by different communication networks.

As shown in Figure 4, an intelligent retrieval device provided by an embodiment of the present application includes:

Obtain module 401, used to obtain the text input by the user;

The reading module 402 is configured to read the text identifier in the document library corresponding to the text input by the user in the pre-established inverted index list based on the text input by the user, and compare the text identifier read from the inverted index list with the text input by the user. The text identifier in the document library corresponding to the text entered by the user is stored in a two-dimensional array;

The calculation module 403 is used to calculate the matching degree between the text corresponding to the text identifier in the document library stored in the two-dimensional array and the text input by the user one by one;

The output module 404 is used to determine the text whose matching degree meets the preset requirements as the search result corresponding to the text input by the user, and output it.

FIG. 5 is a schematic diagram of an electronic device provided by an embodiment of the present application.

Referring to FIG. 5 , a schematic structural diagram of an electronic device suitable for implementing an embodiment of the present application is shown. Electronic devices in embodiments of the present application may include, but are not limited to, fixed terminals such as mobile phones, notebook computers, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, and the like. The electronic device shown in FIG. 5 is only an example and should not impose any restrictions on the functions and scope of use of the embodiments of the present application.

As shown in Figure 5, the electronic device may include a processing device (such as a central processing unit, a graphics processor, etc.) 501, which may be loaded into a random access memory according to a program stored in a read-only memory (ROM) 502 or from a storage device 508. The program in the memory (RAM) 503 is retrieved to execute various appropriate actions and processes. When the electronic device is powered on, RAM 503 also stores various programs and data required for the operation of the electronic device. The processing device 501, the ROM 502 and the RAM 503 are connected to each other via a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.

Generally, the following devices may be connected to the I/O interface 505: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; including, for example, a liquid crystal display (LCD), speakers, vibration An output device 507 such as a computer; a storage device 508 including a memory card, a hard disk, etc.; and a communication device 509. The communication device 509 may allow the electronic device to communicate wirelessly or wiredly with other devices to exchange data. Although FIG. 5 illustrates an electronic device having various means, it should be understood that implementation or availability of all illustrated means is not required. More or fewer means may alternatively be implemented or provided.

In the context of this application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media may include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media would include one or more wire-based electrical connections, laptop disks, hard drives, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.

It should be noted that the computer-readable medium mentioned above in this application may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the above two. The computer-readable storage medium may be, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or any combination thereof. More specific examples of computer readable storage media may include, but are not limited to: electrical connections having one or more conductors, portable computer disks, hard drives, random access memory (RAM), read only memory (ROM), removable Programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above. As used herein, a computer-readable storage medium may be any tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, in which computer-readable program code is carried. Such propagated data signals may take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device . Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wire, optical cable, RF (radio frequency), etc., or any suitable combination of the above.

Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are merely example forms of implementing the claims.

Although several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the application. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.

The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Persons skilled in the art should understand that the disclosure scope involved in this application is not limited to technical solutions composed of specific combinations of the above technical features, but should also cover solutions consisting of the above technical features or without departing from the above disclosed concept. Other technical solutions formed by any combination of equivalent features. For example, a technical solution is formed by replacing the above features with technical features with similar functions disclosed in this application (but not limited to).

Claims (10)

1. An intelligent retrieval method, characterized by including: Get the text entered by the user; According to the text input by the user, the text identifier in the document library corresponding to the text input by the user in the pre-established inverted index list is read, and the text identifier read from the inverted index list corresponding to the text input by the user is read. The text identifier in the document library corresponding to the text input by the user is stored in a two-dimensional array; Calculate the matching degree between the text corresponding to the text identifier in the document library stored in the two-dimensional array and the text input by the user one by one; The text whose matching degree meets the preset requirements is determined as a search result corresponding to the text input by the user, and is output. 2. The intelligent retrieval method according to claim 1, characterized in that the process of pre-establishing an inverted index list includes: Extract key information of each text in the document library, where the key information includes: keywords or keywords; Generate an inverted index list corresponding to each text in the document library, where the inverted index list includes the key information and a text identifier corresponding to the key information. 3. The intelligent retrieval method according to claim 1, characterized in that the text identifier in the document library corresponding to the text input by the user and read from the inverted index list is stored in two Dimensional arrays include: The text in the document library read from the inverted index is stored in the row information of the two-dimensional array, and each row of information in the two-dimensional array represents each text information in the document library; The length information of the text in the document library read from the inverted index is stored in the column information of the two-dimensional array, and each column information in the two-dimensional array represents each text in the document library. length information. 4. The intelligent retrieval method according to claim 1, wherein calculating the matching degree between the text corresponding to the text identifier in the document library stored in the two-dimensional array and the text input by the user one by one includes: Calculate respectively the maximum common string length of the text corresponding to the text input by the user and the text identifier in the document library stored in the two-dimensional array, where the maximum common string length is the sum of the text input by the user and the text identifier stored in the two-dimensional array. The same and continuous field lengths between the texts corresponding to the text identifiers in the document library stored in the two-dimensional array; Using the maximum common substring length, the text length input by the user, and the text length corresponding to the text identifier in the document library stored in the two-dimensional array, the text input by the user and the two-dimensional array are calculated. The matching degree of the text corresponding to the text identifier in the document library stored in . 5. The intelligent retrieval method according to claim 4, characterized in that the use of the maximum common substring length and the text length input by the user and the text identifier in the document library stored in the two-dimensional array The corresponding text length, the calculated matching degree between the text corresponding to the text identifier in the document library stored in the two-dimensional array and the text input by the user includes: The matching degree is calculated by the formula for calculating the matching degree. The formula for calculating the matching degree is: Wherein, the length(lcs) is the maximum common substring length, the length(a) is the text length input by the user, and the length(b) is the document library stored in the two-dimensional array. The text length corresponding to the text identifier. 6. The intelligent retrieval method according to claim 1, wherein determining the text whose matching degree meets the preset requirements includes: Determine the matching degree of the text corresponding to the text identifier in the document library stored in the two-dimensional array and the text input by the user, and use the text with the highest matching degree as the determined matching degree that meets the preset requirements text; or; Determine whether the matching degree corresponding to the text with the highest matching degree exceeds a set threshold; Wherein, if it is determined that the matching degree corresponding to the text with the highest matching degree exceeds the set threshold, then the text with the highest matching degree will be used as the determined text whose matching degree meets the preset requirements; If it is determined that the matching degree corresponding to the text with the highest matching degree does not exceed the set threshold, then this retrieval will fail. 7. The intelligent retrieval method according to claim 1, further comprising: Obtaining the document name list information corresponding to the text in the document library read from the inverted index, and obtaining the two-dimensional representation of the text in the document library read from the inverted index. The position relationship corresponding to the last text in each row in the array that matches the text input by the user is stored in a two-dimensional array. 8. An intelligent retrieval device, characterized by comprising: Get module, used to get the text input by the user; A reading module, configured to read the text identifier in the document library corresponding to the text input by the user in the pre-established inverted index list based on the text input by the user, and read the text identifier from the inverted index list The read text identifier in the document library corresponding to the text input by the user is stored in a two-dimensional array; A calculation module configured to calculate the matching degree between the text corresponding to the text identifier in the document library stored in the two-dimensional array and the text input by the user one by one; An output module is used to determine the text whose matching degree meets the preset requirements as a retrieval result corresponding to the text input by the user, and output it. 9. An electronic device, characterized by comprising at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is configured to execute the computer program so that the electronic device can implement the intelligent retrieval method according to any one of claims 1 to 7. 10. A computer storage medium, characterized in that the storage medium carries one or more computer programs, and when the one or more computer programs are executed by an electronic device, the electronic device can implement the claims as claimed in The intelligent retrieval method described in any one of 1 to 7.