Digital archive data management system

Abstract

A digital archive data management system comprises a user terminal, a server, a data acquisition module, an authority distribution module, an access identification module, an access sorting module, an access tracking module and a cloud database. According to the digital archive data management system, through registration and login, accurate tracking and identification of identities are ensured, responsibility state information of visitors is collected, visit values are obtained through quantitative assignment processing, permission range type levels are matched according to the visit values, and visitors can only access data in an authorized range; then the access state of the digital archive file is intelligently analyzed, abnormity is monitored in real time, an access limiting instruction is triggered, a target access person is optimally selected in combination with multi-dimensional data, meanwhile, the access behavior state of the access person can be monitored in real time, the digital archive file is pushed in a personalized mode, the safety of the digital archive file is guaranteed, and the user experience is improved. And furthermore, the query and calling efficiency of the visitors is improved, and the use experience of the user is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, in particular to a digital archive data management system. Background Art

[0002] With the rapid development of information technology, the archives management of power enterprises has gradually realized the transformation from traditional paper archives to digital archives. Digital archives are stored in electronic form and accessed through the Internet, which greatly improves the efficiency of archive query and retrieval and provides more convenient services for access personnel.

[0003] However, this transformation has also brought about a series of security challenges. The primary issue is the confidentiality of digital archives. Compared with traditional paper archives, digital archives are easier to copy and disseminate, which increases the risk of unauthorized access and leakage. Therefore, how to ensure that each user can only access the archives within their authorized scope and prevent information leakage has become an important security challenge facing power companies.

[0004] Secondly, the integrity and stability of digital archive files are also issues that power companies need to address. As digital archive files are frequently accessed, data loss, damage, and instability may occur. Ensuring the continued availability and accuracy of archive files is also an important security challenge facing power companies. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a digital archive data management system, which improves the security, efficiency and continuous availability of digital archive files.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] A digital archive data management system, comprising

[0008] User terminal, used for access personnel to register and log into the system after entering personal information;

[0009] The server is used to store personal information, the type and level of the permission range matched by the access personnel, the number of access limits and target access personnel corresponding to each abnormal digital archive file in the current monitoring period, and the digital archive files that can be pushed;

[0010] The data collection module is used to collect the duty status information of the access personnel and send the duty status information to the authority allocation module;

[0011] The authority allocation module is used to receive the duty status information of the access personnel, thereby performing authority range matching analysis on the access personnel, obtaining the authority range type level matched by the access personnel, and matching the digital archive files of the corresponding range according to the authority range type level;

[0012] The access identification module is used to monitor the access status information of each digital archive file, thereby analyzing and processing the access status of each digital archive file, obtaining the number of visitors corresponding to each abnormal digital archive file in the current monitoring period, and sending it to the access sorting module;

[0013] The access sorting module is used to receive the number of visitors corresponding to each abnormal digital archive file in the current monitoring period, thereby performing visitor selection analysis and processing on each abnormal digital archive file in the current monitoring period to obtain the target visitor of each abnormal digital archive file in the current monitoring period;

[0014] The access tracking module is used to monitor the access behavior status information of the access personnel, thereby performing personalized push analysis and processing of the digital archive files of the access personnel to obtain pushable digital archive files.

[0015] The authority allocation module performs authority range matching analysis on access personnel, including:

[0016] 1) Obtain the department, position and rank in the duty status information of the visitor, and perform value analysis on the department, position and rank to obtain the department value, position value and rank value of the visitor, and mark them as bm, zw and zj respectively;

[0017] 2) Take its value and obtain the first weighted value dyz1 according to the formula: dyz1 = bm × a1 + zw × a2 + zj × a3, where a1, a2, and a3 are weight coefficients set according to actual needs;

[0018] 3) Obtain the types of projects involved in the visitor's responsibility status information, including large projects, medium-sized projects and small projects. At the same time, obtain the number of times and the degree of responsibility of the project type involved, and mark them as the reference frequency value cs respectively. c and the depth value fz c ; c represents the number of the participating project type, and c=1, 2, 3. When c=1, it represents a large project; when c=2, it represents a medium-sized project; when c=3, it represents a small project.

[0019] 4) According to the formula:

[0020]

[0021] , get the second weight norm value dyz2;

[0022] Among them: b1, b2, b3, b4, b5, b6 are weight coefficients set according to actual needs, μ1, μ2 and μ3 represent the set correction coefficients respectively; cs1 represents the reference frequency value for participating in large-scale projects, cs2 represents the reference frequency value for participating in medium-scale projects, and cs3 represents the reference frequency value for participating in small-scale projects; fz1 represents the reference depth value for participating in large-scale projects, fz2 represents the reference depth value for participating in medium-scale projects, and fz3 represents the reference depth value for participating in small-scale projects;

[0023] 5) Extract the values ​​of the first weighted norm value dyz1 and the second weighted norm value dyz2 for normalization according to the formula: Obtain the visit matching value FPZ of the visitor, wherein e represents a natural constant, η1 and η2 represent weight coefficients of the first weight norm value and the second weight norm value respectively;

[0024] If FPZ<F1, the access personnel's matching authority range is the third-level authority range;

[0025] If F1≤FPZ<F2, the access personnel's matching authority range is the secondary authority range;

[0026] If FPZ ≥ F2, the access personnel's matching authority range is the first-level authority range;

[0027] Among them, F1 and F2 are both access matching thresholds with fixed values, and 0<F1<F2; at the same time, the first-level authority range>the second-level authority range>the third-level authority range; the first-level authority range, the second-level authority range and the third-level authority range constitute the type level of the authority range matched by the access personnel.

[0028] The access identification module analyzes and processes the access status of each digital archive file, including:

[0029] 1) Obtain the number of clicks, transport rate and access duration of each digital archive file in the current monitoring period, extract the three values ​​for normalization, and obtain the access status evaluation value of each digital archive file;

[0030] 2) Compare and analyze the access status evaluation value of each digital archive file with the access status evaluation threshold value. If the access status evaluation value of each digital archive file is greater than or equal to the access status evaluation threshold value FY, an access abnormality signal is generated;

[0031] 3) Marking the digital archive file that captures the abnormal access signal as an abnormal digital archive file, thereby obtaining each abnormal digital archive file in the current monitoring period;

[0032] 4) According to the access abnormality signal generated by each abnormal digital archive file in the current monitoring period, the access restriction instruction is triggered. According to the triggered access restriction instruction, the access status evaluation value of each abnormal digital archive file in the current monitoring period is retrieved, and the access status evaluation value of each abnormal digital archive file in the current monitoring period is calculated by difference with the access status evaluation threshold to obtain the access limit value of each abnormal digital archive file in the current monitoring period;

[0033] 5) The access limit value of each abnormal digital archive file in the current monitoring period is compared and matched with the access limit status determination table stored in the cloud database, thereby obtaining the access limit status level of each abnormal digital archive file in the current monitoring period, and the access limit value of each abnormal digital archive file in the current monitoring period corresponds to an access limit status level, and at the same time, it is matched with the number of access limit persons corresponding to the access limit status level to obtain the number of access limit persons corresponding to each abnormal digital archive file in the current monitoring period.

[0034] The access sorting module performs personnel selection analysis and processing on each abnormal digital archive file in the current monitoring period, including:

[0035] 1) By acquiring the location information of the access personnel, the location information of the access personnel is obtained, and the access personnel within the geographical location range that is allowed to access the abnormal digital archive file are marked as optional access personnel;

[0036] 2) Obtain the click time value, visit history value and second weight norm value of the optional visitor, and mark them as dsz, lfz and dyz2 respectively;

[0037] 3) Extract the three values ​​for normalization according to the formula: Get the preferred value PXA of the selectable visitor; where: β1, β2 and β3 represent the proportional coefficients of the click time value, the history visit value and the second weight norm value respectively;

[0038] 4) By obtaining the preferred values ​​of the optional access personnel for each abnormal digital archive file in the current monitoring period, the optional access personnel arrangement table is obtained by arranging them in descending order according to the numerical values ​​of the preferred values;

[0039] 5) In the list of optional visitors, starting from the highest preferred value, select the optional visitors that match the visit limit number corresponding to each abnormal digital archive file in turn, and mark the successfully selected optional visitors as the target visitors for each abnormal digital archive file in the current monitoring period.

[0040] The access tracking module performs personalized push analysis and processing of digital archive files for access personnel, including:

[0041] 1) Obtain the number of return visits, length of stay, and number of deep hits of each digital archive file by the visitor during the current monitoring period, and mark them as hfz p 、tsz p and sjz p , p represents the number of each digital archive file, p=1, 2, 3...n, n represents the total number of digital archive file numbers;

[0042] 2) And extract the values ​​of the three for normalization processing formula:

[0043] Get the visit value W p 1;

[0044] Where: hfz p * 、tsz p * and sjz p * denote the reference number of return visits, reference length of stay, and reference number of deep hits, respectively; δ1, δ2, and δ3 denote the weight coefficients of the number of return visits, length of stay, and number of deep hits, respectively;

[0045] 3) Compare and analyze the visit tendency value of the visitor to each digital archive file during the current monitoring period with the preset visit tendency threshold value;

[0046] 4) When the access tendency value of the access personnel to access each digital archive file during the current monitoring period is greater than the preset access tendency threshold, the digital archive file is determined as an access tendency digital archive file;

[0047] 5) At the same time, extract the subject text data of the access tendency digital archive file, remove irrelevant characters, punctuation marks and stop words in the text data, and reassemble and segment the removed text data into words for sorting;

[0048] 6) Count the number of occurrences of related words after segmentation, and sort them from high to low according to word frequency, set a word frequency threshold, mark words with a word frequency greater than the word frequency threshold as target words, extract the duration and click times of the visitor's visit to the target words in the current monitoring period, multiply them by the corresponding weight coefficients, and then add them to get the visit demand value, recorded as W p 2;

[0049] 7) Extract the visitor's visit inclination value W p 1 and the visit demand value is recorded as W p 2 is normalized according to the formula: TJZ = W p 1×Ψ1+W p 2×Ψ2, and get the comprehensive visit value TJZ;

[0050] Where: Ψ1 and Ψ2 represent the weight coefficients of the visit behavior value and the visit demand value, respectively, and Ψ1>Ψ2;

[0051] 8) Compare and analyze the comprehensive visit tendency value with the preset comprehensive visit tendency threshold; if the comprehensive visit tendency value is greater than or equal to the preset comprehensive visit tendency threshold, personalized push of digital archive files is performed;

[0052] 9) By comparing and analyzing the comprehensive visit inclination value of the visitor with the comprehensive visit inclination status determination table stored in the cloud database, the comprehensive visit inclination status level of the visitor is obtained, and the comprehensive visit inclination value of each visitor corresponds to a comprehensive visit inclination status level. At the same time, it is matched with the digital archive file corresponding to the comprehensive visit inclination status level to obtain a pushable digital archive file.

[0053] The present invention provides a digital archive data management system, which has the following technical effects:

[0054] 1) Register and log in personal information through the user terminal to ensure that the identity of each visitor can be accurately tracked and identified; collect the duty status information of the visitor with authorization through the data collection module; and quantify and assign values ​​to this information according to the set rules and algorithms used by the authority allocation module to obtain the access matching value, and match the visitor with the corresponding authority range type level accordingly; at the same time, match the digital archive files of the corresponding range according to the authority range type level, so as to ensure that the visitor can only access the information within his authorized scope, greatly improving the security of the digital archive files.

[0055] 2) Through the access identification module, the number of clicks, transport rate and access time of each digital archive file are intelligently analyzed, so as to monitor and evaluate the access status of each digital archive file in real time and provide data support for abnormal status detection. Once an abnormality is found, the access restriction instruction will be triggered quickly to automatically limit the number of visitors to prevent potential security risks. Combined with the access sorting module, the location information, click time value, historical access data and the second weight norm value of the access personnel are comprehensively analyzed and processed to optimize the selection of access personnel, thereby achieving not only improving access efficiency, but also ensuring the continuous availability and accuracy of archive files, and improving the security of digital archive files;

[0056] 3) By real-time monitoring and analyzing the access behavior status information of visitors through the access tracking module, it is possible to understand the user's tendencies and needs, and push digital archive files that meet their needs. This not only effectively responds to the above-mentioned security challenges, but also can personalize the push of digital archive files based on the access behavior status information of visitors, thereby improving the query and retrieval efficiency of visitors and optimizing the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The present invention will be further described below in conjunction with the accompanying drawings and embodiments:

[0058] Figure 1 It is an overall block diagram of the present invention. DETAILED DESCRIPTION

[0059] like Figure 1 As shown, a digital archive data management system includes: a user terminal, a server, a data acquisition module, a permission allocation module, an access identification module, an access sorting module, an access tracking module and a cloud database.

[0060] The user terminal is used for the visitor to register and log into the system after entering personal information, and send the personal information to the server, wherein the personal information includes the visitor's name, ID number, and mobile phone number.

[0061] The cloud database is used to store an access restriction status determination table and a comprehensive access tendency status determination table.

[0062] The server is connected to a data collection module. After the visitor is authorized and agreed, the data collection module is used to collect the duty status information of the visitor and send the duty status information to the authority allocation module through the server.

[0063] It should be noted that ensuring that explicit authorization has been obtained from the access personnel is accomplished by having the access personnel perform corresponding confirmation operations on the system interface.

[0064] The responsibility status information includes the department, position, rank, number of project types participated in and the degree of responsibility of the accessing personnel.

[0065] The authority allocation module is used to receive the duty status information of the access personnel, and then conduct authority range matching analysis on the access personnel, including:

[0066] 1) Obtain the department, position and rank in the duty status information of the visiting personnel, and perform value analysis on the department, position and rank to obtain the department value, position value and rank value of the visiting personnel, and mark them as bm, zw and zj respectively.

[0067] In 1) above, the department, position and rank are assigned values, including:

[0068] The specific assignment of the department is: set the department name of the access personnel and the department value corresponding to the department name, match the corresponding department name according to the department of the access personnel, and then extract the corresponding department value according to the department name. For example, the department value corresponding to the equipment maintenance department is q1, the department value corresponding to the power transmission department is q2, and the department value corresponding to the power generation department is q3.

[0069] The specific assignment of positions is: set the position name of the visiting person and the position value corresponding to the position name, match the corresponding position name according to the visiting person's position, and then extract the corresponding position value according to the position name. For example, the position value corresponding to the security specialist is w1, the position value corresponding to the supervisor is w2, and the position value corresponding to the manager is w3.

[0070] The specific assignment of job grades is: set the job grade name of the visiting personnel and the job grade value corresponding to the job grade name, match the corresponding job grade name according to the job grade of the visiting personnel, and then extract the corresponding job grade value according to the job grade name. For example, the job grade value corresponding to the junior level is e1, the job grade value corresponding to the intermediate level is e2, and the job grade value corresponding to the senior level is e3.

[0071] Among them, the more important the department, the greater the assigned value, and the higher the position and rank, the greater the assigned value. The specific assignment settings of departments, positions and ranks are made by technical personnel in this field in specific cases.

[0072] 2) Take its numerical value and obtain the first weight value dyz1 according to the formula: dyz1=bm×a1+zw×a2+zj×a3, where a1, a2, and a3 are weight coefficients set according to actual needs.

[0073] 3) Obtain the types of projects involved in the visitor's responsibility status information, including large projects, medium-sized projects and small projects. At the same time, obtain the number of times and the degree of responsibility of the project type involved, and mark them as the reference frequency value cs respectively. c and the depth value fz c , c represents the number of the participating project type, and c = 1, 2, 3;

[0074] When c=1, it indicates a large project, when c=2, it indicates a medium-sized project, and when c=3, it indicates a small project.

[0075] 4) According to the formula:

[0076]

[0077] , get the second weight norm value dyz2;

[0078] Among them: b1, b2, b3, b4, b5, b6 are weight coefficients set according to actual needs, μ1, μ2 and μ3 represent the set correction coefficients respectively, cs1 represents the frequency parameter value for participating in large-scale projects, cs2 represents the frequency parameter value for participating in medium-sized projects, cs3 represents the frequency parameter value for participating in small-scale projects; fz1 represents the depth parameter value for participating in large-scale projects, fz2 represents the depth parameter value for participating in medium-sized projects, fz3 represents the depth parameter value for participating in small-scale projects.

[0079] It should be noted that the reference depth value fz c Refers to an indicator that measures the importance of the interviewer's responsibilities in the project he / she participates in. The specific solution process is: by obtaining the number of important decisions made by the interviewer in the project he / she participates in, the number of working days he / she is responsible for, and the area of ​​responsibility scope, and at the same time extracting the number of important decisions made by the interviewer in the project he / she participates in, the number of working days he / she is responsible for, and the area of ​​responsibility scope, multiplying the values ​​by the corresponding weight coefficients and then adding them to get the depth value;

[0080] 5) Extract the values ​​of the first weighted norm value dyz1 and the second weighted norm value dyz2 for normalization according to the formula: Get the visitor's visit matching value FPZ;

[0081] Wherein: e represents a natural constant, η1 and η2 represent the weight coefficients of the first weight norm value and the second weight norm value respectively, and η1>η2. The weight coefficient is used to balance the weight of each data in the formula calculation, thereby promoting the accuracy of the calculation result.

[0082] If FPZ<F1, the access personnel's matching authority range is the third-level authority range;

[0083] If F1≤FPZ<F2, the access personnel's matching authority range is the secondary authority range;

[0084] If FPZ ≥ F2, the access personnel's matching authority range is the first-level authority range;

[0085] The level of permission range type matched by the access personnel is composed of the first level permission range, the second level permission range and the third level permission range;

[0086] Among them, F1 and F2 are both access matching thresholds with fixed values, and 0<F1<F2. At the same time, the first-level authority range>the second-level authority range>the third-level authority range.

[0087] For example, the access matching value interval of the third-level authority range is [0, 20), the access matching value interval of the second-level authority range is [20, 30), and the access matching value interval of the first-level authority range is [30, ∞]. If the access matching value is 25, and the access matching value interval to which the access matching value belongs is [20, 30), then the type level of the authority range matched by the access personnel is the second-level authority range.

[0088] The authority allocation module feeds back the authority range type level matched by the access personnel to the server, and the server matches the digital archive files of the corresponding range according to the authority range type level.

[0089] The access identification module is used to monitor the access status information of each digital archive file, thereby analyzing and processing the access status of each digital archive file, specifically including:

[0090] 1) By obtaining the number of clicks, carrying rate and access duration of each digital archive file in the current monitoring period, the number of clicks, carrying rate and access duration of each digital archive file in the current monitoring period are obtained; and they are marked as djz j 、ysl j and fwz j , extract the three values ​​for normalization; according to the formula: Get the access status evaluation value FWP of each digital archive file j ;

[0091] Among them, γ1, γ2 and γ3 represent the weight coefficients of the number of clicks, carrying rate and access time respectively, and γ1>γ2>γ3. The weight coefficients are used to balance the weight of each data in the formula calculation, thereby promoting the accuracy of the calculation results.

[0092] 2) Set the access status evaluation threshold of each digital archive file to FY, and set the access status evaluation value FWP of each digital archive file to j Comparison analysis with the access status assessment threshold FY:

[0093] If the access status evaluation value FWP of each digital archive file j When it is greater than or equal to the access status evaluation threshold FY, an access abnormality signal is generated;

[0094] If the access status evaluation value FWP of each digital archive file j When it is less than the access status evaluation threshold FY, an access normal signal is generated.

[0095] 3) The digital archive file that captures the abnormal access signal is marked as an abnormal digital archive file, thereby obtaining each abnormal digital archive file in the current monitoring period.

[0096] 4) Based on the access exception signal generated by each abnormal digital archive file in the current monitoring period, the access restriction instruction is triggered; based on the triggered access restriction instruction, the access status evaluation value of each abnormal digital archive file in the current monitoring period is retrieved; and the access status evaluation value of each abnormal digital archive file in the current monitoring period is calculated by difference with the access status evaluation threshold to obtain the access limit value of each abnormal digital archive file in the current monitoring period.

[0097] 5) The access limit value of each abnormal digital archive file in the current monitoring period is compared and matched with the access limit status determination table stored in the cloud database, thereby obtaining the access limit status level of each abnormal digital archive file in the current monitoring period, and the access limit value of each abnormal digital archive file in the current monitoring period corresponds to an access limit status level, and at the same time, it is matched with the number of access limit persons corresponding to the access limit status level to obtain the number of access limit persons corresponding to each abnormal digital archive file in the current monitoring period.

[0098] The access identification module feeds back the number of visitors corresponding to each abnormal digital archive file in the current monitoring period to the server, and the server sends the number of visitors corresponding to each abnormal digital archive file in the current monitoring period to the access sorting module.

[0099] The access sorting module is used to receive the number of visitors corresponding to each abnormal digital archive file in the current monitoring period, and thereby perform visitor selection analysis and processing on each abnormal digital archive file in the current monitoring period, specifically including:

[0100] 1) By acquiring the location information of the visitor, the location information of the visitor is obtained, and the visitor who is located in the geographical location range allowed to access the abnormal digital archive file is marked as an optional visitor.

[0101] 2) Obtain the click time value, visit history value and second weight norm value of the optional visitor, and mark them as dsz, lfz and dyz2 respectively.

[0102] 3) Extract the three values ​​for normalization according to the formula: Obtain the preferred value PXA of the optional visitor;

[0103] Among them: β1, β2 and β3 represent the proportional coefficients of click time value, visit value and second weight value respectively, and β1>β2>β3. The proportional coefficient is used to balance the weight of each data in the formula calculation, so as to promote the accuracy of the calculation result.

[0104] It should be noted that the click time value refers to the time point when the visitor clicks or views the abnormal digital archive file, and the history visit value refers to the number of times the visitor has visited the abnormal digital archive file in the past.

[0105] 4) By obtaining the preferred values ​​of the optional access personnel for each abnormal digital archive file in the current monitoring period, the optional access personnel arrangement table is obtained by arranging them in descending order according to the numerical values ​​of the preferred values.

[0106] 5) In the list of optional visitors, starting from the highest preferred value, select the optional visitors that match the visit limit number corresponding to each abnormal digital archive file in turn, and mark the successfully selected optional visitors as the target visitors for each abnormal digital archive file in the current monitoring period.

[0107] The access sorting module feeds back the target access personnel of each abnormal digital archive file in the current monitoring period to the server, and the target access personnel of each abnormal digital archive file in the current monitoring period are displayed and notified on the user terminal through the server.

[0108] The access tracking module is used to monitor the access behavior status information of the access personnel, thereby performing personalized push analysis and processing of digital archive files for the access personnel, specifically including:

[0109] 1) By obtaining the number of return visits, length of stay and number of deep hits of each digital archive file visited by the visitor during the current monitoring period, the number of return visits, length of stay and number of deep hits of each digital archive file visited by the visitor during the current monitoring period are obtained, and they are marked as hfz p 、tsz p and sjz p , p represents the number of each digital archive file, p=1, 2, 3...n, n represents the total number of digital archive file numbers.

[0110] 2) And extract the values ​​of the three for normalization processing formula:

[0111] Get the visit value W p 1;

[0112] Where: hfz p * 、tsz p * and sjz p * They represent the reference number of return visits, reference length of stay and reference number of deep hits respectively. δ1, δ2 and δ3 represent the weight coefficients of the number of return visits, length of stay and number of deep hits respectively. The weight coefficients are used to balance the proportion of each data in the formula calculation, so as to promote the accuracy of the calculation results.

[0113] It should be noted that the number of return visits indicates the number of times a visitor visits a certain digital archive file again, which reflects the extent of the visitor's inquiry into a certain digital archive file; the length of stay indicates the length of time a visitor stays on a certain digital archive file page. By analyzing the length of stay of visitors, we can understand the visitor's attention to a certain digital archive file; the number of deep clicks indicates how many different pages a visitor clicks on when visiting a certain digital archive file, which reflects their depth of understanding of the content.

[0114] 3) Compare and analyze the access tendency value of the access personnel to each digital archive file during the current monitoring period with the preset access tendency threshold.

[0115] 4) When the access tendency value of the access personnel to access each digital archive file during the current monitoring period is greater than the preset access tendency threshold, the digital archive file is determined to be an access tendency digital archive file.

[0116] 5) At the same time, extract the subject text data of the access tendency digital archive file. The text data can be a group of words, a group of comments and a paragraph. Remove irrelevant characters, punctuation marks and stop words in the text data, and reassemble and split the removed text data into words for sorting.

[0117] 6) Count the number of occurrences of related words after segmentation, and sort them from high to low according to word frequency, set a word frequency threshold, mark words with a word frequency greater than the word frequency threshold as target words, extract the duration and click times of the visitor's visit to the target words in the current monitoring period, multiply them by the corresponding weight coefficients, and then add them to get the visit demand value, recorded as W p 2.

[0118] 7) Extract the visitor's visit inclination value W p 1 and the visit demand value is recorded as W p 2 is normalized according to the formula: TJZ = W p 1×Ψ1+W p 2×Ψ2, and get the comprehensive visit value TJZ;

[0119] Wherein: Ψ1 and Ψ2 represent the weight coefficients of the visit behavior inclination value and the visit demand inclination value respectively, and Ψ1>Ψ2.

[0120] 8) Compare and analyze the comprehensive visit tendency value with the preset comprehensive visit tendency threshold. If the comprehensive visit tendency value is greater than or equal to the preset comprehensive visit tendency threshold, personalized push of digital archive files is performed.

[0121] 9) By comparing and analyzing the comprehensive visit inclination value of the visitor with the comprehensive visit inclination status determination table stored in the cloud database, the comprehensive visit inclination status level of the visitor is obtained, and the comprehensive visit inclination value of each visitor corresponds to a comprehensive visit inclination status level. At the same time, it is matched with the digital archive file corresponding to the comprehensive visit inclination status level to obtain a pushable digital archive file.

[0122] The access tracking module feeds back the pushable digital archive file to the server, and the server displays the pushable digital archive file on the user terminal for notification.

Claims

1. A digital archive data management system, characterized in that: include User terminal, used for access personnel to register and log into the system after entering personal information; The server is used to store personal information, the type and level of the permission range matched by the access personnel, the number of access limits and target access personnel corresponding to each abnormal digital archive file in the current monitoring period, and the digital archive files that can be pushed; The data collection module is used to collect the duty status information of the access personnel and send the duty status information to the authority allocation module; The authority allocation module is used to receive the duty status information of the access personnel, thereby performing authority range matching analysis on the access personnel, obtaining the authority range type level matched by the access personnel, and matching the digital archive files of the corresponding range according to the authority range type level; The access identification module is used to monitor the access status information of each digital archive file, thereby analyzing and processing the access status of each digital archive file, obtaining the number of visitors corresponding to each abnormal digital archive file in the current monitoring period, and sending it to the access sorting module; The access sorting module is used to receive the number of visitors corresponding to each abnormal digital archive file in the current monitoring period, thereby performing visitor selection analysis and processing on each abnormal digital archive file in the current monitoring period to obtain the target visitor of each abnormal digital archive file in the current monitoring period; The access tracking module is used to monitor the access behavior status information of the access personnel, thereby performing personalized push analysis and processing of the digital archive files of the access personnel to obtain pushable digital archive files.

2. A digital archive data management system according to claim 1, characterized in that: The authority allocation module performs authority range matching analysis on access personnel, including: 1) Obtain the department, position and rank in the duty status information of the visitor, and perform value analysis on the department, position and rank to obtain the department value, position value and rank value of the visitor, and mark them as bm, zw and zj respectively; 2) Take its value and obtain the first weighted value dyz1 according to the formula: dyz1 = bm × a1 + zw × a2 + zj × a3, where a1, a2, and a3 are weight coefficients set according to actual needs; 3) Obtain the types of projects involved in the visitor's responsibility status information, including large projects, medium-sized projects and small projects. At the same time, obtain the number of times and the degree of responsibility of the project type involved, and mark them as the reference frequency value cs respectively. c and the depth value fz c ; c represents the number of the participating project type, and c=1, 2, 3. When c=1, it represents a large project; when c=2, it represents a medium-sized project; when c=3, it represents a small project. 4) According to the formula: ， Get the second weight norm value dyz2; Among them: b1, b2, b3, b4, b5, b6 are weight coefficients set according to actual needs, μ1, μ2 and μ3 represent the set correction coefficients respectively; cs1 represents the reference frequency value for participating in large-scale projects, cs2 represents the reference frequency value for participating in medium-scale projects, and cs3 represents the reference frequency value for participating in small-scale projects; fz1 represents the reference depth value for participating in large-scale projects, fz2 represents the reference depth value for participating in medium-scale projects, and fz3 represents the reference depth value for participating in small-scale projects; 5) Extract the values ​​of the first weighted norm value dyz1 and the second weighted norm value dyz2 for normalization according to the formula: Obtain the visit matching value FPZ of the visitor, wherein e represents a natural constant, η1 and η2 represent weight coefficients of the first weight norm value and the second weight norm value respectively; If FPZ<F1, the access personnel's matching authority range is the third-level authority range; If F1≤FPZ<F2, the access personnel's matching authority range is the secondary authority range; If FPZ ≥ F2, the access personnel's matching authority range is the first-level authority range; Among them, F1 and F2 are both access matching thresholds with fixed values, and 0<F1<F2; at the same time, the first-level authority range>the second-level authority range>the third-level authority range; the first-level authority range, the second-level authority range and the third-level authority range constitute the type level of the authority range matched by the access personnel.

3. A digital archive data management system according to claim 1, characterized in that: The access identification module analyzes and processes the access status of each digital archive file, including: 1) Obtain the number of clicks, transport rate and access duration of each digital archive file in the current monitoring period, extract the three values ​​for normalization, and obtain the access status evaluation value of each digital archive file; 2) Compare and analyze the access status evaluation value of each digital archive file with the access status evaluation threshold value. If the access status evaluation value of each digital archive file is greater than or equal to the access status evaluation threshold value FY, an access abnormality signal is generated; 3) Marking the digital archive file that captures the abnormal access signal as an abnormal digital archive file, thereby obtaining each abnormal digital archive file in the current monitoring period; 4) According to the access abnormality signal generated by each abnormal digital archive file in the current monitoring period, the access restriction instruction is triggered. According to the triggered access restriction instruction, the access status evaluation value of each abnormal digital archive file in the current monitoring period is retrieved, and the access status evaluation value of each abnormal digital archive file in the current monitoring period is calculated by difference with the access status evaluation threshold to obtain the access limit value of each abnormal digital archive file in the current monitoring period; 5) The access limit value of each abnormal digital archive file in the current monitoring period is compared and matched with the access limit status determination table stored in the cloud database, thereby obtaining the access limit status level of each abnormal digital archive file in the current monitoring period, and the access limit value of each abnormal digital archive file in the current monitoring period corresponds to an access limit status level, and at the same time, it is matched with the number of access limit persons corresponding to the access limit status level to obtain the number of access limit persons corresponding to each abnormal digital archive file in the current monitoring period.

4. A digital archive data management system according to claim 1, characterized in that: The access sorting module performs access personnel selection analysis and processing on each abnormal digital archive file in the current monitoring period, including: 1) By acquiring the location information of the access personnel, the location information of the access personnel is obtained, and the access personnel within the geographical location range that is allowed to access the abnormal digital archive file are marked as optional access personnel; 2) Obtain the click time value, visit history value and second weight norm value of the optional visitor, and mark them as dsz, lfz and dyz2 respectively; 3) Extract the three values ​​for normalization according to the formula: Get the preferred value PXA of the selectable visitor; where: β1, β2 and β3 represent the proportional coefficients of the click time value, the history visit value and the second weight norm value respectively; 4) By obtaining the preferred values ​​of the optional access personnel for each abnormal digital archive file in the current monitoring period, the optional access personnel arrangement table is obtained by arranging them in descending order according to the numerical values ​​of the preferred values; 5) In the list of optional visitors, starting from the highest preferred value, select the optional visitors that match the visit limit number corresponding to each abnormal digital archive file in turn, and mark the successfully selected optional visitors as the target visitors for each abnormal digital archive file in the current monitoring period.

5. A digital archive data management system according to claim 1, characterized in that: The access tracking module performs personalized push analysis and processing of digital archive files for access personnel, including: 1) Obtain the number of return visits, length of stay, and number of deep hits of each digital archive file by the visitor during the current monitoring period, and mark them as hfz p 、tsz p and sjz p , p represents the number of each digital archive file, p=1, 2, 3...n, n represents the total number of digital archive file numbers; 2) And extract the values ​​of the three for normalization processing formula: Get the visit value W p 1; Among them: hfz p * 、tsz p * and sjz p * denote the reference number of return visits, reference length of stay, and reference number of deep hits, respectively; δ1, δ2, and δ3 denote the weight coefficients of the number of return visits, length of stay, and number of deep hits, respectively; 3) Compare and analyze the visit tendency value of the visitor to each digital archive file during the current monitoring period with the preset visit tendency threshold value; 4) When the access tendency value of the access personnel to access each digital archive file during the current monitoring period is greater than the preset access tendency threshold, the digital archive file is determined as an access tendency digital archive file; 5) At the same time, extract the subject text data of the access tendency digital archive file, remove irrelevant characters, punctuation marks and stop words in the text data, and reassemble and segment the removed text data into words for sorting; 6) Count the number of occurrences of related words after segmentation, and sort them from high to low according to word frequency, set a word frequency threshold, mark words with a word frequency greater than the word frequency threshold as target words, extract the duration and click times of the visitor's visit to the target words in the current monitoring period, multiply them by the corresponding weight coefficients, and then add them to get the visit demand value, recorded as W p 2; 7) Extract the visitor's visit inclination value W p 1 and the visit demand value is recorded as W p 2 is normalized according to the formula: TJZ = W p 1×Ψ1+W p 2×Ψ2, and get the comprehensive visit value TJZ; Where: Ψ1 and Ψ2 represent the weight coefficients of the visit behavior value and the visit demand value, respectively, and Ψ1>Ψ2; 8) Compare and analyze the comprehensive visit tendency value with the preset comprehensive visit tendency threshold; if the comprehensive visit tendency value is greater than or equal to the preset comprehensive visit tendency threshold, personalized push of digital archive files is performed; 9) By comparing and analyzing the comprehensive visit inclination value of the visitor with the comprehensive visit inclination status determination table stored in the cloud database, the comprehensive visit inclination status level of the visitor is obtained, and the comprehensive visit inclination value of each visitor corresponds to a comprehensive visit inclination status level. At the same time, it is matched with the digital archive file corresponding to the comprehensive visit inclination status level to obtain a pushable digital archive file.

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