An enterprise user report recommendation and correction method and system

Abstract

The present invention relates to a method and system for recommending and correcting enterprise user reports, belonging to the technical field of report applications, and solves the problem that existing technologies cannot intelligently recommend and correct reports according to users. It includes: obtaining a list of recommended industry model reports according to keywords input by the user, adding the selected industry model reports to the user report library, and increasing the recommendation value of the selected industry model reports; modifying any user report in the user report library, setting configuration items of the user report, publishing and sharing the user report, and recording user behavior logs; calculating the recommendation value of the shared report based on the user behavior logs, and displaying the shared reports in descending order of the recommendation value; regularly correcting the default configuration items of the corresponding industry model reports according to the configuration items with high repetition rates; regularly correcting the report structure of the industry model reports according to the report structure with high repetition rates. The accurate recommendation and continuous optimization of reports are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of report applications, and in particular, to a method and system for recommending and correcting enterprise user reports. Background Art

[0002] With the increasing requirements for data analysis, each enterprise issues various different data reports every month. In order to improve the generation efficiency of data reports, online tools are generally used to design templates and obtain data in real time or regularly, gradually replacing manual report editing.

[0003] Existing online editing tools are generally customized and generated by report designers according to historical report styles, extracting report templates and then according to the needs of each department. This often results in reports that cannot timely display the data required by users, and report designers always complain that the report styles are always changing; and when there are more and more report templates, it will also increase the selection difficulty for report designers or users.

[0004] The main reason for this problem is that the design and use of reports are separated. Report designers cannot know or do not pay attention to the usage of reports, cannot correct the general settings of reports in advance according to users' usage habits, and the provided report templates do not conform to users' needs, with low pertinence and applicability, and it is difficult to respond to users' needs in a timely manner. Summary of the Invention

[0005] In view of the above analysis, embodiments of the present invention aim to provide a method and system for recommending and correcting enterprise user reports to solve the problem that existing reports cannot be intelligently recommended and corrected according to users' usage.

[0006] On the one hand, embodiments of the present invention provide a method for recommending and correcting enterprise user reports, including the following steps:

[0007] According to the keywords input by the user, obtain a list of recommended industry model reports, add the selected industry model report to the user report library, and increase the recommendation value of the selected industry model report;

[0008] Modify any user report in the user report library, set the configuration items of the user report, publish and share the user report, and record the user behavior log;

[0009] Based on the user behavior log, calculate the recommendation value of the shared report, and display the shared reports in descending order of the recommendation value;

[0010] Regularly count the configuration items of user reports, and correct the default configuration items of the corresponding industry model reports according to the configuration items with high repetition rates;

[0011] Regularly count the differences in the report structures between each industry model report and the associated user reports, and correct the report structure of the industry model report according to the report structures with high repetition rates.

[0012] Based on further improvements to the above method, the industry model report is a pre-set report with the same report structure, report attributes, and storage form as the user report. Among them,

[0013] The report structure is encapsulated in Html format, and the embedded elements are defined using DIV and type IDs. The embedded elements include: report title, text body, charts, pictures, videos, and data items;

[0014] The report attributes include: report identifier, report name, report remarks, report tags, belonging directory, report creator, configuration items, and recommended values. The configuration items include: sharing role, sharing organization, sharing users, recommended period, recommended date, and recommended time;

[0015] The storage form includes: metadata, chart files, report attribute data, analysis data, reference relationships, and indexes.

[0016] Based on further improvements to the above method, obtain a list of recommended industry model reports according to the keywords input by the user, including:

[0017] Initialize the thesaurus, including: business thesaurus and semantic-free thesaurus;

[0018] Set the search index items and corresponding weights, including: report title, text body, charts, report remarks, report tags, belonging directory;

[0019] Based on the thesaurus, after segmenting the keywords input by the user, match the segmented keywords with the values of the search index items, and summarize the product of the matching degree and weight of each index item in each industry model report to obtain the recommendation score for each industry model report;

[0020] Based on the recommendation scores and recommended values of each industry model report, obtain a list of recommended industry model reports.

[0021] Based on further improvements to the above method, share user reports, including:

[0022] Based on the association relationships between roles and users, and between organizations and users, obtain the set of sharing users according to the sharing role, sharing organization, and sharing users in the configuration items of the user report;

[0023] If the set of sharing users is not empty, regularly obtain the user report and push it to the users in the set of sharing users according to the recommended period, recommended date, and recommended time; if the set of sharing users is empty, only the report creator can view the published user report.

[0024] Based on the further improvement of the above method, user behavior logs are recorded, which are the logs of each user's operation of the user report, including the following behavior metrics:

[0025] Editing duration: Record the cumulative duration from receiving the design command to saving the user report;

[0026] Reading duration: Record the cumulative duration from opening the user report to closing the user report;

[0027] Printing times: Record the cumulative number of times the user report is printed;

[0028] Downloading times: Record the cumulative number of times the user report is downloaded;

[0029] Reading times: Record the cumulative number of times the user report is opened;

[0030] Sharing times: Record the cumulative number of times the user report is shared.

[0031] Based on the further improvement of the above method, based on the user behavior logs, the recommended value of the shared report is calculated, including:

[0032] Taking each shared report as a dimension, summarize the values of each behavior metric respectively to obtain the total value of each behavior metric for each shared report;

[0033] Based on the preset scoring criteria, calculate the scores of each behavior metric for each shared report according to the total value of each behavior metric;

[0034] Multiply the scores of each behavior metric by the preset weights of each behavior metric, and then sum them up to obtain the recommended value of each shared report.

[0035] Based on the further improvement of the above method, users can also search for shared reports by keywords, and obtain the recommended shared reports based on the recommended scores and recommended values of each shared report obtained from the search.

[0036] Based on the further improvement of the above method, if the user is a user in the shared user group, the user can also select any shared user report and add the template to their own user report library.

[0037] Based on the further improvement of the above method, correct the report structure of the industry model report according to the report structure with high repetition rate. It is to count the number of references of the embedded elements in the associated user report structure with the industry model report as the dimension according to the report structure and the stored reference relationship, select the embedded element with the most references, and cover the embedded elements with the same type ID in the report structure of the industry model report.

[0038] On the other hand, an embodiment of the present invention provides an enterprise user report recommendation and correction system, including:

[0039] The industry model report management module is used to obtain a list of recommended industry model reports according to keywords input by users, maintain industry model reports, export industry model reports, and import report templates;

[0040] The user report design module is used to manage user reports and design user reports, including adding the industry model reports selected by users to the user report library; selecting any shared user report and adding a template to the user report library; modifying any user report in the user report library, setting the configuration items of the user report, and publishing and sharing user reports;

[0041] The user report sharing module is used to manage shared user reports, including querying shared reports, reading, printing, collecting, importing / exporting, and adding templates to any shared report;

[0042] The user behavior log management module is used to record user behavior logs, including editing duration, reading duration, printing times, downloading times, reading times, and sharing times;

[0043] The recommendation correction module calculates the recommendation value of shared reports based on user behavior logs; regularly counts the repetition rate of user-level configuration items and corrects the default configuration items according to the configuration items with a high repetition rate; regularly counts the report structure difference items between each industry model report and the associated user reports, and corrects the report structure of the industry model report according to the report structure with a high repetition rate.

[0044] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0045] 1. By analyzing the report sharing scope and recommendation frequency at the user level, obtaining configuration items with a high repetition rate, continuously correcting the default configuration items of the industry model report, and correcting the report structure of the industry model report by comparing the differences between user reports and industry model reports, it continuously approaches the actual user usage habits, reduces the secondary correction workload of users, and improves the value of enterprise user reports;

[0046] 2. By recording and analyzing different user behavior logs, counting the usage of user reports, extracting behavior indicators that reflect long usage time and high usage frequency of user reports, and calculating the recommendation value, the accuracy of user report recommendation is improved;

[0047] 3. During the entire life cycle of the report, the monitoring and analysis of report usage are increased, the report configuration items and report structure are continuously optimized, and each user-personalized report operation is fed back to the optimization process of the industry model report, truly realizing the closed-loop management of the report and forming a virtuous cycle.

[0048] In the present invention, the above technical solutions may also be combined with each other to achieve more preferred combination solutions. Other features and advantages of the present invention will be described in the following specification. Moreover, some advantages will become apparent from the specification or can be understood by implementing the present invention. The objectives and other advantages of the present invention can be realized and obtained from the content specifically pointed out in the specification and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The drawings are only for the purpose of showing specific embodiments and are not considered as a limitation to the present invention. Throughout the drawings, the same reference signs denote the same components.

[0050] Figure 1 It is a flowchart of the enterprise user report recommendation and correction method in Embodiment 1 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0051] The following will specifically describe the preferred embodiments of the present invention with reference to the drawings. The drawings form a part of this application and are used together with the embodiments of the present invention to explain the principles of the present invention, rather than to limit the scope of the present invention.

[0052] Embodiment 1,

[0053] A specific embodiment of the present invention discloses an enterprise user report recommendation and correction method, as Figure 1 shown, which includes the following steps:

[0054] S11: According to the keywords input by the user, obtain a list of recommended industry model reports, add the selected industry model reports to the user report library, and increase the recommendation value of the selected industry model reports;

[0055] It should be noted that the industry model reports are pre-set business reports, which have the same report structure, report attributes, and storage form as the user reports. Among them,

[0056] The report structure is encapsulated in Html format, and the embedded elements are defined by DIV and type IDs. The embedded elements include: report title, text body, charts, pictures, videos, and data items;

[0057] The report attributes include: report identifier, report name, report remarks, report tags, directory, report creator, configuration items, and recommendation value. The configuration items include: sharing roles, sharing organizations, sharing users, recommendation periods, recommendation dates, and recommendation times;

[0058] According to the types of the elements in the report structure, the report is decomposed into different storage forms for easy analysis and retrieval. The storage forms include: metadata, chart files, report attribute data, analysis data, reference relationships, and indexes.

[0059] Preferably, different storage forms use different storage services. For example, metadata and report attribute data are stored in relational databases, chart files are stored in HDFS (Hadoop Distributed File System) file servers, analysis data is stored in ClickHouse, reference relationships use Neo4j graph database, which supports query and analysis of blood relationships, and indexes use Elasticsearch search engine to index key information and support full-text search to quickly locate data.

[0060] The difference between an industry model report and a user report is that the data items in an industry model report are static sample data, while the data items in a user report are dynamic data, and data is obtained in real time or periodically based on the data fields associated with the data items in the user report.

[0061] When building a report, users can select an industry model report as a basic report and then modify it to a user report. When selecting an industry model report, a list of recommended industry model reports is obtained based on the keywords entered by the user. During the search process, on the one hand, the keywords entered by the user are segmented and analyzed, and the results are matched through full-text search. On the other hand, the recommendation list is displayed in the order that is closest to the user's usage habits to improve the accuracy of the recommendation.

[0062] Specifically, you need to initialize the vocabulary first, including: business vocabulary and non-semantic vocabulary; business vocabulary is related to the business field, such as "finance, funds, assets", and non-semantic vocabulary is punctuation marks and words without specific meanings, such as "space, comma, semicolon, de", which are used to remove unnecessary information in keywords during word segmentation, thereby improving retrieval efficiency and matching degree.

[0063] Preferably, an approximate matching tuple may be preset, and related keywords may be obtained by approximate matching to achieve accurate recommendation. For example, "fixed assets, asset analysis" approximates "assets".

[0064] Next, according to the report attributes, set the index items and corresponding weights for search, including: report title, text body, charts, report notes, report tags, and the directory to which it belongs;

[0065] Preferably, the keywords searched by the user are recorded, and the keywords with high frequency are counted after word segmentation, the word library is updated, and the corresponding index items are added. For example, the keywords with high frequency are counted and involve "day and month", and the recommended period is added to the index item while the word library is updated.

[0066] When performing a search, based on the thesaurus, after segmenting the keywords entered by the user, the segmented keywords are matched with the values of the search index terms, and the product of the matching degree and weight of each index term in each industry model report is summarized to obtain the recommendation score of each industry model report;

[0067] Based on the recommendation scores and recommendation values of each industry model report, a list of recommended industry model reports is obtained.

[0068] It should be noted that the recommendation value of the industry model report is initially preset according to the business analysis results. Subsequently, according to the user's selection, whenever it is selected as the basis for the user report, the recommendation value increases by 1. When the recommendation scores obtained from the search are the same, the searched industry model reports are sorted secondarily from largest to smallest according to the recommendation value.

[0069] When the user selects one or more from the list of recommended industry model reports and adds them to their own user report, according to the storage form of the report, the information of the selected industry model report will be copied and stored in the user report, and an association relationship between the user report and the industry model report will be established.

[0070] S12: Modify any user report in the user report library, set the configuration items of the user report, publish and share the user report, and record the user behavior log;

[0071] It should be noted that since the industry model report is static sample data, generally, the user needs to adjust or customize the report structure for the selected industry model report, including: binding a new data set; matching fields, adding custom fields, and adding custom filtering conditions according to the set data set; adjusting the user report style, report title, and report text; adjusting or adding charts, tables, pictures, and videos.

[0072] After the report content design is completed, the user sets the configuration items of the user report according to the default configuration items. Those related to the sharing scope include: selecting sharing roles, sharing organizations, and sharing users; those related to the recommendation frequency include: recommendation period, recommendation date, and recommendation time;

[0073] After the setting is completed, save the configuration items of the user report, and record the creator and creation time of the user report;

[0074] After the user report is published, it is no longer allowed to be modified. After canceling the publication, it can be modified again;

[0075] When the user report is published, based on the association relationships between roles and users, and between organizations and users, according to the sharing roles, sharing organizations, and sharing users in the configuration items of the user report, obtain the set of sharing users;

[0076] If the set of sharing users is not empty, regularly obtain user reports according to the recommendation period, recommendation date, and recommendation time, and push them to the users in the set of sharing users; if the set of sharing users is empty, only the report creator can view the published user reports.

[0077] Preferably, the push of user reports is realized through the report push process. The sharing role, sharing organization, and sharing users or the obtained set of users are used as the executors who can view user reports in the process. The report push process is regularly started according to the recommendation frequency to send a to-do message to remind the shared users to view the user reports, or through the timeout warning of the process to remind the users to complete the viewing. This way can not only enable users to view reports in a timely manner but also collect the behavior logs of each user to ensure the integrity of information collection and improve the accuracy of subsequent report correction.

[0078] Users can also completely customize a user report, and there is no associated industry model report at this time.

[0079] S13: Calculate the recommended value of the shared report based on the user behavior logs, and display the shared reports in descending order of the recommended value.

[0080] Users can view the user reports they shared and the user reports they were shared with, and can view, print, collect, import / export, and add templates to the user reports. In order to correct user reports more accurately and closer to user usage habits, the user behavior logs are recorded to track and analyze the user's usage situation.

[0081] Recording user behavior logs means recording the logs of each user's operation on the user report, including the following behavior metrics:

[0082] Editing duration: Record the cumulative duration from receiving the design command to saving the user report;

[0083] Reading duration: Record the cumulative duration from opening the user report to closing the user report;

[0084] Printing times: Record the cumulative number of times the user report is printed;

[0085] Downloading times: Record the cumulative number of times the user report is downloaded;

[0086] Reading times: Record the cumulative number of times the user report is opened;

[0087] Sharing times: Record the cumulative number of times the user report is shared.

[0088] Specifically, based on the user behavior logs, the calculated recommended value of the shared report includes:

[0089] Taking each sharing report as a dimension, summarize the numerical values of each behavior indicator respectively to obtain the total value of each behavior indicator for each sharing report;

[0090] Exemplarily, analyze the sharing report A involved in the user behavior log, and summarize and count the total values of each behavior indicator of 10 users: editing duration 600 seconds, reading duration 1200 seconds, printing times 5 times, downloading times 6 times, reading times 30 times, sharing times 5 times.

[0091] Based on the preset scoring criteria, calculate the scores of each behavior indicator for each sharing report according to the total values of each behavior indicator;

[0092] Exemplarily, the scoring criteria for duration are: 0 - 50 seconds, score value is 5; 50 - 100 seconds, score value is 10; 100 - 500 seconds, score value is 20; above 500 seconds, score value is 50; the scoring criteria for times are: the number of times is the score; then the scores of each behavior indicator are: editing duration 50 points, reading duration 50 points, printing times 5 points, downloading times 6 points, reading times 30 points, sharing times 5 points.

[0093] Multiply the scores of each behavior indicator by the preset weights of each behavior indicator, and then sum them up to obtain the recommendation value of each sharing report.

[0094] Exemplarily, the indicator weights of the preset editing duration, reading duration, printing times, downloading times, reading times and sharing times are 5%, 20%, 20%, 20%, 25%, 10% respectively, then the recommendation value of sharing report A is: 50×5% + 50×20% + 5×20% + 6×20% + 30×25% + 5×10% = 22.7 points.

[0095] Preferably, the sharing report can also be searched according to the keywords input by the user. Similar to the method of searching for industry model reports, based on the recommendation scores of each sharing report obtained by searching, and the recommendation value of the sharing report calculated according to the user behavior log, the recommended sharing report is obtained.

[0096] The user can also select any shared user report and add a template to their own user report library.

[0097] It should be noted that when the user selects any shared user report and chooses to add a template to their own user report library, the report structure, configuration items and associated industry model report identifiers of the selected user report will be copied as a new user report record and associated with the current user.

[0098] Any user report in the user report library can be exported as a zip file package, including a report structure file and a data file in Json format. Correspondingly, the user can also import the user report structure file into their own user report library. When importing, according to the user report ID in the report structure file, obtain the corresponding configuration items and the associated industry model report ID, and encapsulate them into a new user report according to the storage form of the report, associating with the current user.

[0099] Preferably, user reports with high recommendation values can also be exported, and the user report structure file can be imported into the industry model report to facilitate the expansion of the industry model report and increase the model report assets.

[0100] S14: Regularly count the configuration items of user reports, and correct the default configuration items of the corresponding industry model report according to the configuration items with high repetition rates;

[0101] Specifically, count the configuration items of user reports that reference the same industry model report, calculate the quantity of each setting in the configuration items, and update the setting of the default configuration item in the industry model report according to the setting with the largest quantity.

[0102] Exemplarily, 10 user reports are associated with industry model report A. Among them, the "sharing role" of 6 user reports is set to "section chief", the "sharing role" of 3 user reports is set to "director", and the "sharing role" of 1 user report is set to "specialist". If the default "sharing role" of industry model report A is not "section chief", then it is updated to "section chief".

[0103] Because the needs of users are also constantly changing, regular corrections can adapt to the changes, reduce the workload of secondary corrections for users, and improve the response timeliness rate.

[0104] S15: Regularly count the report structure difference items between each industry model report and the associated user reports, and correct the report structure of the industry model report according to the report structure with high repetition rates.

[0105] Considering that the industry model report is a report initially created based on business analysis, with the development and adjustment of the business, the initial model report may no longer be applicable. If waiting for users to raise demands before making adjustments, it can only respond passively. Therefore, by regularly counting the report structures of user reports, changing from passive to active, timely correcting the industry model report, improving user satisfaction and usability, and making user reports more valuable.

[0106] Specifically, correcting the report structure of the industry model report according to the report structure with high repetition rates is to count the reference times of the embedded elements in the associated user report structure with the industry model report as the dimension according to the report structure and the storage reference relationship, select the embedded element with the most reference times, and cover the embedded elements with the same type ID in the report structure of the industry model report.

[0107] Preferably, the reported citation relationships adopt a graph database to record the relationships between the charts, data sets, user reports, and industry model reports cited in the reports. By querying the paths to the nodes, the number of times a node is cited can be obtained.

[0108] Exemplarily, industry model report B is associated with 10 user reports. Among them, 7 user reports cite line charts, and 3 user reports cite pie charts. If the pie chart initially cited in industry model report B is cited, then the pie chart in industry model report B is corrected to a line chart.

[0109] Compared with the prior art, this embodiment provides a method for recommending and correcting enterprise user reports. By recording the industry model reports selected by users, the recommendation value of the industry model reports is increased; by recording and analyzing different user behavior logs, the usage of user reports is statistically analyzed, behavior indicators reflecting long usage time and high usage frequency of user reports are extracted, and the recommendation value is calculated to improve the accuracy of user report recommendation; by analyzing the report sharing scope and recommendation frequency at the user level, configuration items with high repetition rates are obtained, and the default configuration items of the industry model reports are continuously corrected. By comparing the differences between user reports and industry model reports, the report structure of the industry model reports is corrected, continuously approaching the actual user usage habits, reducing the secondary correction workload of users, promoting the virtuous cycle of user report recommendation and usage, and enhancing the value of enterprise user reports.

[0110] Embodiment 2

[0111] This embodiment provides an enterprise user report recommendation and correction system to implement the recommendation and correction method in Embodiment 1. The specific implementation methods of each module refer to the corresponding descriptions in Embodiment 1. The system includes:

[0112] An industry model report management module, which is used to obtain a list of recommended industry model reports according to the keywords input by users, maintain industry model reports, export industry model reports, and import report templates;

[0113] A user report design module, which is used to manage user reports and design user reports, including adding the industry model reports selected by users to the user report library; selecting any shared user report and adding a template to the user report library; modifying any user report in the user report library, setting the configuration items of the user report, and publishing and sharing the user report;

[0114] A user report sharing module, which is used to manage shared user reports, including querying shared reports, reading, printing, collecting, importing / exporting, and adding templates to any shared report;

[0115] User Behavior Log Management Module, which is used to record user behavior logs, including editing duration, reading duration, printing times, downloading times, reading times and sharing times;

[0116] Recommendation and Correction Module, which calculates the recommended value of the sharing report based on the user behavior logs; regularly counts the repetition rate of user-level configuration items, and corrects the default configuration items according to the configuration items with high repetition rate; regularly counts the report structure difference items between each industry model report and the associated user report, and corrects the report structure of the industry model report according to the report structure with high repetition rate.

[0117] Compared with the prior art, the present embodiment provides an enterprise user report recommendation and correction system. In the report construction, through intelligent recommendation, accurate industry model reports are introduced. Through user report sharing, the use of user reports is promoted. At the same time, the monitoring and analysis of report usage are increased, the report configuration items and report structures are continuously optimized, and each step of user personalized report operation is fed back to the optimization process of the industry model report, truly realizing the closed-loop management of the report, forming a virtuous cycle, and gradually improving the accuracy of recommendation and the fitting degree of use.

[0118] Those skilled in the art can understand that all or part of the processes of implementing the above method embodiments can be completed by instructing relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. Among them, the computer-readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory, etc.

[0119] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention.

Claims

1. A method for recommending and correcting enterprise user reports, characterized in that, It includes the following steps: According to the keywords input by the user, obtain a list of recommended industry model reports, add the selected industry model report to the user report library, and increase the recommendation value of the selected industry model report; Modify any user report in the user report library, set the configuration items of the user report, publish and share the user report, and record the user behavior log; Based on the user behavior log, calculate the recommendation value of the shared report, and display the shared report in descending order of the recommendation value; Regularly count the configuration items of the user report, and correct the default configuration items of the corresponding industry model report according to the configuration items with high repetition rate; Regularly count the report structure difference items between each industry model report and the associated user report, and correct the report structure of the industry model report according to the report structure with high repetition rate; The user behavior log includes multiple behavior indicators; calculating the recommendation value of the shared report based on the user behavior log includes: taking each shared report as a dimension, respectively summarizing the values of each behavior indicator to obtain the total value of each behavior indicator of each shared report; based on a preset scoring standard, calculating the score of each behavior indicator of each shared report according to the total value of each behavior indicator; multiplying the scores of each behavior indicator by the preset weights of each behavior indicator and then adding them up to obtain the recommendation value of each shared report.

2. The method for recommending and correcting enterprise user reports according to claim 1, characterized in that, The industry model report is a preset report, which has the same report structure, report attributes and storage form as the user report, where The report structure is encapsulated in Html format, and the embedded elements are defined by DIV and type ID. The embedded elements include: report title, text body, chart, picture, video, data item; The report attributes include: report identifier, report name, report remarks, report tags, belonging directory, report creator, configuration items and recommendation value. The configuration items include: sharing role, sharing organization, sharing user, recommendation period, recommendation date and recommendation time; The storage form includes: metadata, chart file, report attribute data, analysis data, reference relationship and index.

3. The method for recommending and correcting enterprise user reports according to claim 2, characterized in that, The obtaining of the list of recommended industry model reports according to the keywords input by the user includes: Initialize the thesaurus, including: business thesaurus and non-semantic thesaurus; Set the search index items and corresponding weights, including: report title, text body, chart, report remarks, report tags, belonging directory; After segmenting the keywords input by the user based on the thesaurus, match the segmented keywords with the values of the search index items, and summarize the product of the matching degree and weight of each index item in each industry model report to obtain the recommendation score of each industry model report; Based on the recommendation score and recommendation value of each industry model report, obtain a list of recommended industry model reports.

4. The method for recommending and correcting enterprise user reports according to claim 3, characterized in that, The sharing of the user report includes: Based on the association relationship between roles and users, and organizations and users, obtain the set of sharing users according to the sharing role, sharing organization and sharing user in the configuration items of the user report; If the set of sharing users is not empty, regularly obtain user reports according to the recommended period, recommended date, and recommended time, and push them to the users in the set of sharing users; if the set of sharing users is empty, only the report creator can view the published user reports.

5. The method for recommending and correcting enterprise user reports according to any one of claims 1-4, characterized in that, The recording of user behavior logs is to record the logs of each user's operation of user reports, including the following behavior metrics: Editing duration: Record the cumulative duration from receiving the design command to saving the user report; Reading duration: Record the cumulative duration from opening the user report to closing the user report; Number of prints: Record the cumulative number of times the user report is printed; Number of downloads: Record the cumulative number of times the user report is downloaded; Number of reads: Record the cumulative number of times the user report is opened; Number of shares: Record the cumulative number of times the user report is shared.

6. The method for recommending and correcting enterprise user reports according to claim 5, characterized in that, The user can also search for shared reports by keywords, and obtain the recommended shared reports based on the recommended scores and the recommended values of the shared reports obtained by the search.

7. The method for recommending and correcting enterprise user reports according to claim 6, characterized in that, If the user is a user in the set of sharing users, the user can also select any shared user report and add a template to their own user report library.

8. The method for recommending and correcting enterprise user reports according to claim 2, characterized in that, The modification of the report structure of the industry model report according to the report structure with a high repetition rate is to, based on the report structure and the stored reference relationships, take the industry model report as the dimension, count the reference times of the embedded elements in the associated user report structures, select the embedded element with the most reference times, and overwrite the embedded elements with the same type ID in the report structure of the industry model report.

9. An enterprise user report recommendation and correction system, characterized in that Including: Industry model report management module, used to obtain a list of recommended industry model reports according to the keywords input by the user, maintain industry model reports, export industry model reports, and import report templates; User report design module, used to manage user reports and design user reports, including adding the industry model report selected by the user to the user report library; selecting any shared user report and adding a template to the user report library; Modifying any user report in the user report library, setting the configuration items of the user report, publishing and sharing the user report; User report sharing module, used to manage shared user reports, including querying shared reports, reading, printing, collecting, importing / exporting, and adding templates to any shared report; User behavior log management module, used to record user behavior logs, including editing duration, reading duration, number of prints, number of downloads, number of reads, and number of shares; Recommendation correction module, which calculates the recommended value of the shared report based on the user behavior logs; Regularly count the repetition rate of the configuration items of the user report, and correct the default configuration items according to the configuration items with a high repetition rate; Regularly count the report structure difference items between each industry model report and the associated user reports, and correct the report structure of the industry model report according to the report structure with a high repetition rate; The user behavior log includes multiple behavior metrics; calculating a recommended value of a sharing report based on the user behavior log includes: taking each sharing report as a dimension, respectively aggregating the values of the behavior metrics to obtain the total value of each behavior metric of each sharing report; based on a preset scoring criterion, calculating the score of each behavior metric of each sharing report according to the total value of each behavior metric; multiplying the scores of each behavior metric by the preset weights of each behavior metric and then adding them up to obtain the recommended value of each sharing report.

Images