An information intelligent classification and retrieval system for archives management

Abstract

The present invention relates to the field of archive management technology, and in particular to an information intelligent classification retrieval system for archive management, comprising: a collection module, which is used to collect the number and frequency of clicks of users on information blocks in current search results, the frequency of use of each keyword in the current search results, and the total browsing time of all information blocks in the current search results; a calculation module, which is used to calculate the search evaluation; an acquisition module; a data analysis module; and a display module. In the present invention, whether the information retrieval efficiency is qualified is determined according to the search evaluation, and when the information retrieval efficiency is initially determined to be unqualified, a secondary determination is made on whether the information retrieval efficiency is qualified according to the historical search evaluation, or the reason for the unqualified information retrieval efficiency is determined according to the search evaluation, thereby improving the control accuracy of the information retrieval process, and the data analysis module optimizes the search process according to the analysis result, thereby improving the search efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of archive management, and in particular to an information intelligent classification retrieval system for archive management. Background Art

[0002] With the advent of the era of big data, the amount of information data has greatly increased. Archival information, as an important data material, is extremely important for its management. The existing technology has achieved centralized archiving management of archival data by constructing an archival information resource library and using data as the link between various subsystems. However, due to the large amount of archival information, the retrieval process is complicated and the retrieval efficiency is low.

[0003] Chinese patent application number: CN201710208178.9 discloses a smart archive based on big data, which relates to the field of archive management application technology. By constructing an archive information resource library and using the data of the archive information resource library as the link between each subsystem, each subsystem provides special scenario services for archive management applications, realizing intelligent management and control of archives, accurate archive positioning, enhanced archive reading experience, and intelligent use of archive data, thereby realizing the standardization, refinement, transparency, and intelligence of the archive electronic process, and the rapidity, precision, and diversification of archive retrieval. At the same time, it also realizes the centralized archiving management of archive data, business application subject classification, data clustering management, document content management and application, and cross-departmental data collaboration application. Global management and intelligent application. It can be seen that the smart archive based on big data has the following problems: due to the large amount of archive information, the retrieval process is complicated, and the efficiency of archive information retrieval is low. Summary of the invention

[0004] To this end, the present invention provides an information intelligent classification retrieval system for archive management, which is used to overcome the problem of low efficiency of archive information retrieval in the prior art.

[0005] To achieve the above-mentioned purpose, the present invention provides an information intelligent classification retrieval system for archive management. It includes:

[0006] A collection module, which is used to collect the number and frequency of clicks by users on the information blocks in the current search results, the frequency of use of each keyword in the current search results, and the total browsing time of all information blocks in the current search results;

[0007] A calculation module, connected to the collection module, for calculating the search evaluation according to the collected click quantity and the total browsing time;

[0008] An acquisition module, which is connected to the acquisition module and the calculation module, and is used to acquire historical search evaluations in historical records;

[0009] a data analysis module connected to the acquisition module, the calculation module and the acquisition module, for determining whether the information retrieval efficiency is qualified according to the retrieval evaluation calculated by the calculation module, and for performing a secondary determination on whether the information retrieval efficiency is qualified according to the historical retrieval evaluation when the information retrieval efficiency is determined to be unqualified, or determining the reason why the information retrieval efficiency is unqualified according to the retrieval evaluation;

[0010] The display module is connected to the data analysis module and is used to receive keywords sent by the data analysis module.

[0011] Further, the data analysis module determines whether the information retrieval efficiency is qualified according to the retrieval evaluation calculated by the calculation module, and,

[0012] When it is initially determined that the information retrieval efficiency is unqualified, a secondary determination is made on whether the information retrieval efficiency is qualified based on the historical retrieval evaluation, or the reason why the information retrieval efficiency is unqualified is determined based on the retrieval evaluation.

[0013] Furthermore, the calculation module calculates the retrieval evaluation S based on the number of clicks A collected by the collection module and the total browsing time T, and sets the retrieval evaluation S = a×A0 / A+t×T / T0, where a is the click weight coefficient, t is the time weight coefficient, a+t=1, A0 is the preset number of clicks preset in the data analysis module, and T0 is the preset total browsing time preset in the data analysis module.

[0014] Further, the acquisition module acquires the historical search evaluation in the historical record, and the data analysis module determines whether the information retrieval efficiency is qualified according to the absolute value of the difference between the acquired historical search evaluation and the search evaluation, and adjusts the preset total browsing time to a corresponding value according to the difference between the historical search evaluation and the search evaluation when the information retrieval efficiency is determined to be qualified, or,

[0015] When it is determined that the information retrieval efficiency is unqualified, the reason why the information retrieval efficiency is unqualified is determined based on the retrieval evaluation.

[0016] Furthermore, when the data analysis module determines to adjust the preset total browsing time to a corresponding value based on the difference between the historical retrieval evaluation and the retrieval evaluation, the difference between the historical retrieval evaluation and the retrieval evaluation is recorded as a first-level difference, and based on the first-level difference, several correction methods for the preset total browsing time are provided, and the correction range of each correction method for the preset total browsing time is different.

[0017] Furthermore, when determining the reason why the information retrieval efficiency is unqualified based on the retrieval evaluation, the data analysis module determines the reason why the information retrieval efficiency is unqualified based on the ratio of the retrieval evaluation to a second preset retrieval evaluation preset in the data analysis module, or, makes a secondary determination on the reason why the information retrieval efficiency is unqualified based on the click frequency, and the reasons include: unreasonable information field screening and a small range of information retrieval keywords.

[0018] Furthermore, when the data analysis module makes a secondary determination on the reasons why the information retrieval efficiency is unqualified based on the click frequency, the reasons for determining that the information retrieval efficiency is unqualified based on the click frequency include: unreasonable information field screening and a small range of information retrieval keywords.

[0019] Furthermore, when the data analysis module determines that the reason for the unqualified information retrieval efficiency is unreasonable information field screening, it determines whether the keyword meets the prompt standard according to the usage frequency of a single keyword in the current search result.

[0020] Furthermore, the data analysis module screens out the keywords currently input for retrieval when determining that the keywords meet the prompt standard, and sends the keywords to the display module when the screening is completed.

[0021] Furthermore, when the data analysis module determines that the reason for the unsatisfactory information retrieval efficiency is that the information retrieval keyword range is small, it determines whether the information block meets the retrieval criteria based on the click frequency of the information block containing the keyword in the historical records, and, when it is determined that the information block meets the retrieval criteria, adds the information block to the retrieval results.

[0022] Compared with the prior art, the beneficial effect of the present invention lies in that the data analysis module in the present invention determines whether the information retrieval efficiency is qualified based on the retrieval evaluation, and when the information retrieval efficiency is initially determined to be unqualified, a secondary determination is made on whether the information retrieval efficiency is qualified based on the historical retrieval evaluation, or the reason why the information retrieval efficiency is unqualified is determined based on the retrieval evaluation, thereby improving the control accuracy of the information retrieval process, and the data analysis module optimizes the retrieval process based on the analysis results, thereby improving the retrieval efficiency.

[0023] Furthermore, the data analysis module in the present invention sets the retrieval evaluation parameters according to the number of clicks and the total browsing time, which further improves the control precision of the information retrieval process and improves the accuracy of analyzing the information retrieval process.

[0024] Furthermore, the data analysis module in the present invention determines whether the information retrieval efficiency is qualified based on the absolute value of the difference between the historical retrieval evaluation and the retrieval evaluation, and adjusts the determination benchmark to a corresponding value based on the difference between the historical retrieval evaluation and the retrieval evaluation when the information retrieval efficiency is determined to be qualified, thereby improving the matching degree between the determination benchmark and the current usage scenario, further improving the analysis accuracy, and further improving the archival information retrieval efficiency.

[0025] Furthermore, the data analysis module in the present invention selects a corresponding correction coefficient according to the difference between the historical search evaluation and the search evaluation to adjust the preset total browsing time to a corresponding value, thereby avoiding inaccurate analysis results due to different personal habits and further improving the analysis accuracy.

[0026] Furthermore, the data analysis module in the present invention determines the reason why the information retrieval efficiency is unqualified based on the ratio of the retrieval evaluation to the second preset retrieval evaluation, thereby further improving the analysis accuracy. The data analysis module optimizes the retrieval process based on the analysis results, thereby further improving the retrieval efficiency.

[0027] Furthermore, the display module in the present invention displays the keywords that are not input during the initial search process, so that the user can update the keywords and search again. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a structural block diagram of the information intelligent classification retrieval system for archive management of the present invention;

[0029] Figure 2 A flowchart for determining whether information retrieval efficiency is qualified in the present invention;

[0030] Figure 3 This is a flow chart of the present invention for modifying the preset total browsing time;

[0031] Figure 4 The present invention is a flow chart for determining the reasons why the information retrieval efficiency is unqualified. DETAILED DESCRIPTION

[0032] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0033] It should be pointed out that the data in this embodiment are obtained by comprehensive analysis and evaluation of the historical data of the system of the present invention in the three months before this determination and the corresponding historical determination results. Before this detection, the system of the present invention comprehensively determines the values ​​of the various preset parameter standards for this determination based on the evaluation values ​​of the 36,283 retrieval results detected cumulatively in the first three months. It can be understood by those skilled in the art that the system of the present invention can determine the single parameter mentioned above by selecting the value with the highest proportion as the preset standard parameter according to the data distribution, using weighted summation to use the obtained value as the preset standard parameter, substituting each historical data into a specific formula and using the value obtained by the formula as the preset standard parameter or other selection methods, as long as the system of the present invention can clearly define the different specific situations in the single determination process through the obtained values.

[0034] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0035] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0036] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0037] See also Figure 1 As shown, it is a structural block diagram of the information intelligent classification and retrieval system for archive management of the present invention.

[0038] The information intelligent classification and retrieval system for archive management according to the embodiment of the present invention comprises:

[0039] A collection module, which is used to collect the number and frequency of clicks by users on the information blocks in the current search results, the frequency of use of each keyword in the current search results, and the total browsing time of all information blocks in the current search results;

[0040] A calculation module, connected to the collection module, for calculating the search evaluation according to the collected click quantity and the total browsing time;

[0041] An acquisition module, which is connected to the acquisition module and the calculation module, and is used to acquire historical search evaluations in historical records;

[0042] a data analysis module connected to the acquisition module, the calculation module and the acquisition module, for determining whether the information retrieval efficiency is qualified according to the retrieval evaluation calculated by the calculation module, and for performing a secondary determination on whether the information retrieval efficiency is qualified according to the historical retrieval evaluation when the information retrieval efficiency is determined to be unqualified, or determining the reason why the information retrieval efficiency is unqualified according to the retrieval evaluation;

[0043] The display module is connected to the data analysis module and is used to receive keywords sent by the data analysis module.

[0044] See also Figure 2 As shown, it is a flow chart of the present invention for determining whether the information retrieval efficiency is qualified.

[0045] Specifically, the data analysis module determines whether the information retrieval efficiency is qualified according to the retrieval evaluation calculated by the calculation module, wherein:

[0046] The first determination method is that the data analysis module determines that the information retrieval efficiency is qualified; the first determination method satisfies that the retrieval evaluation is greater than or equal to the first preset retrieval evaluation preset in the data analysis module;

[0047] The second determination method is that the data analysis module preliminarily determines that the information retrieval efficiency is unqualified, and performs a secondary determination on whether the information retrieval efficiency is qualified based on the historical retrieval evaluation; the second determination method satisfies that the retrieval evaluation is less than the first preset retrieval evaluation and is greater than or equal to the second preset retrieval evaluation preset in the data analysis module;

[0048] The third determination method is that the data analysis module determines that the information retrieval efficiency is unqualified, and determines the reason for the unqualified information retrieval efficiency based on the retrieval evaluation; the third determination method satisfies that the retrieval evaluation is less than the second preset retrieval evaluation.

[0049] In the embodiment of the present invention, the first preset retrieval evaluation is 2.42, and the second preset retrieval evaluation is 0.75.

[0050] The data analysis module in the present invention determines whether the information retrieval efficiency is qualified based on the retrieval evaluation, and when the information retrieval efficiency is initially determined to be unqualified, a secondary determination is made on whether the information retrieval efficiency is qualified based on the historical retrieval evaluation, or the reason why the information retrieval efficiency is unqualified is determined based on the retrieval evaluation, thereby improving the control accuracy of the information retrieval process. The data analysis module optimizes the retrieval process based on the analysis results, thereby improving the retrieval efficiency.

[0051] Specifically, the calculation module calculates the retrieval evaluation S based on the number of clicks A collected by the collection module and the total browsing time T, and sets the retrieval evaluation S = a×A0 / A+t×T / T0, where a is the click weight coefficient, t is the time weight coefficient, a+t=1, A0 is the preset number of clicks preset in the data analysis module, and T0 is the preset total browsing time preset in the data analysis module.

[0052] In the embodiment of the present invention, the click weight coefficient is 0.35, the duration weight coefficient is 0.65, the preset number of clicks is 3 times, and the preset total browsing duration is 3 minutes.

[0053] The data analysis module in the present invention sets the retrieval evaluation parameters according to the number of clicks and the total browsing time, which further improves the control precision of the information retrieval process and improves the accuracy of analyzing the information retrieval process.

[0054] Specifically, the acquisition module acquires the historical retrieval evaluation in the historical record, and the data analysis module determines whether the information retrieval efficiency is qualified according to the absolute value of the difference between the acquired historical retrieval evaluation and the retrieval evaluation, wherein:

[0055] The first qualified judgment method is that the data analysis module determines that the information retrieval efficiency is qualified, and adjusts the preset total browsing time to a corresponding value according to the difference between the historical retrieval evaluation and the retrieval evaluation; the first qualified judgment method satisfies that the absolute value is less than or equal to the preset absolute value preset in the data analysis module;

[0056] The second qualified judgment method is that the data analysis module determines that the information retrieval efficiency is unqualified, and determines the reason for the unqualified information retrieval efficiency based on the retrieval evaluation; the second qualified judgment method satisfies that the absolute value is greater than the preset absolute value.

[0057] The preset absolute value in the embodiment of the present invention is 0.75.

[0058] The data analysis module in the present invention determines whether the information retrieval efficiency is qualified based on the absolute value of the difference between the historical retrieval evaluation and the retrieval evaluation, and adjusts the determination benchmark to the corresponding value based on the difference between the historical retrieval evaluation and the retrieval evaluation when the information retrieval efficiency is determined to be qualified, thereby improving the matching degree between the determination benchmark and the current usage scenario, further improving the analysis accuracy, and further improving the archival information retrieval efficiency.

[0059] See also Figure 3 As shown, it is a flow chart of the present invention for correcting the preset total browsing time.

[0060] Specifically, the data analysis module records the difference between the historical search evaluation and the search evaluation as a primary difference under the first qualification determination method, and determines a correction method for the preset total browsing time according to the primary difference, wherein:

[0061] The first correction method is that the data analysis module selects the first correction coefficient α1 to correct the preset total browsing time to a corresponding value, and sets the corrected preset total browsing time T0'=α1×T0; the first correction method satisfies that the first-level difference is less than or equal to the preset first-level difference preset in the data analysis module;

[0062] The second correction method is that the data analysis module selects the second correction coefficient α2 to correct the preset total browsing time to a corresponding value, and sets the corrected preset total browsing time T0'=α2×T0; the second correction method satisfies that the first-level difference is greater than the preset first-level difference.

[0063] In the embodiment of the present invention, the first correction coefficient α1 is 1.12, the second correction coefficient α2 is 1.24, and the preset first-order difference is 0.5.

[0064] The data analysis module in the present invention selects a corresponding correction coefficient according to the difference between the historical search evaluation and the search evaluation to adjust the preset total browsing time to a corresponding value, thereby avoiding inaccurate analysis results due to different personal habits and further improving the analysis accuracy.

[0065] See also Figure 4 As shown, it is a flow chart of the present invention for determining the reasons why the information retrieval efficiency is unqualified.

[0066] Specifically, the data analysis module records the ratio of the retrieval evaluation to the second preset retrieval evaluation as a primary ratio under the third determination method, and determines the determination method of the reason for the unqualified information retrieval efficiency according to the primary ratio, wherein:

[0067] The first reason determination method is that the data analysis module determines that the reason for the unqualified information retrieval efficiency is unreasonable information field screening; the first reason determination method satisfies that the first-level ratio is less than or equal to the first preset first-level ratio preset in the data analysis module;

[0068] The second reason determination method is that the data analysis module determines the reason for the unqualified information retrieval efficiency to be secondary determined according to the click frequency; the second reason determination method satisfies that the first-level ratio is greater than the first preset first-level ratio and is less than or equal to the second preset first-level ratio preset in the data analysis module;

[0069] The third reason determination method is that the data analysis module determines that the reason why the information retrieval efficiency is unqualified is that the information retrieval keyword range is small; the third reason determination method satisfies that the first-level ratio is greater than the second preset first-level ratio.

[0070] In the embodiment of the present invention, the first preset primary ratio is 0.2, and the second preset primary ratio is 0.4.

[0071] The data analysis module in the present invention determines the reason why the information retrieval efficiency is unqualified based on the ratio of the retrieval evaluation to the second preset retrieval evaluation, thereby further improving the analysis accuracy. The data analysis module optimizes the retrieval process based on the analysis results, thereby further improving the retrieval efficiency.

[0072] Specifically, the data analysis module determines the reason determination method for the unqualified information retrieval efficiency according to the click frequency under the second reason determination method, wherein:

[0073] The first reason determination method is that the data analysis module determines that the reason why the information retrieval efficiency is unqualified is unreasonable information field screening; the first reason determination method satisfies that the click frequency is less than or equal to the preset click frequency preset in the data analysis module;

[0074] The second reason determination method is that the data analysis module determines that the reason why the information retrieval efficiency is unqualified is that the range of information retrieval keywords is small; the second reason determination method satisfies that the click frequency is greater than the preset click frequency.

[0075] In the embodiment of the present invention, the preset click frequency is 3 times / minute.

[0076] Specifically, the data analysis module determines whether the keyword meets the prompt standard according to the usage frequency of a single keyword in the current search results under the first preset condition, wherein:

[0077] The first prompt determination method is that the data analysis module determines that the keyword meets the prompt standard; the first prompt determination method satisfies that the usage frequency is greater than or equal to the preset usage frequency preset in the data analysis module;

[0078] The second prompt determination method is that the data analysis module determines that the keyword does not meet the prompt standard; the second prompt determination method satisfies that the usage frequency is less than the preset usage frequency;

[0079] The first preset condition is that the reason why the data analysis module determines that the information retrieval efficiency is unqualified is that the information field screening is unreasonable.

[0080] In the embodiment of the present invention, the preset usage frequency is 10 times.

[0081] Specifically, the data analysis module screens out the keywords currently input for retrieval in the first prompt determination mode, and sends the keywords to the display module when the screening is completed.

[0082] The display module in the present invention displays the keywords that are not input during the initial search process, so that the user can update the keywords and search again.

[0083] Specifically, the data analysis module determines whether the information block meets the search criteria according to the click frequency of the information block containing the keyword in the historical record under the second preset condition, wherein:

[0084] The first determination method is that the data analysis module determines that the information block meets the search criteria and adds the information block to the search results; the first determination method satisfies that the click frequency is greater than or equal to a preset click frequency preset in the data analysis module;

[0085] The second determination method is that the data analysis module determines that the information block does not meet the search criteria; the second determination method satisfies that the click frequency is less than the preset click frequency;

[0086] The second preset condition is that the reason why the data analysis module determines that the information retrieval efficiency is unqualified is that the range of information retrieval keywords is small.

[0087] In the embodiment of the present invention, the data analysis module makes a determination based on the click frequency of the information block containing the keyword within 90 days in the historical records, and the preset click frequency is 30 times.

[0088] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0089] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An intelligent information classification and retrieval system for archive management, characterized in that: include: A collection module, which is used to collect the number and frequency of clicks by users on the information blocks in the current search results, the frequency of use of each keyword in the current search results, and the total browsing time of all information blocks in the current search results; A calculation module, connected to the collection module, for calculating the search evaluation according to the collected click quantity and the total browsing time; An acquisition module, which is connected to the acquisition module and the calculation module, and is used to acquire historical search evaluations in historical records; a data analysis module connected to the acquisition module, the calculation module and the acquisition module, for determining whether the information retrieval efficiency is qualified according to the retrieval evaluation calculated by the calculation module, and for performing a secondary determination on whether the information retrieval efficiency is qualified according to the historical retrieval evaluation when the information retrieval efficiency is determined to be unqualified, or determining the reason why the information retrieval efficiency is unqualified according to the retrieval evaluation; A display module, which is connected to the data analysis module and is used to receive keywords sent by the data analysis module; The data analysis module determines whether the information retrieval efficiency is qualified according to the retrieval evaluation calculated by the calculation module, and, When the information retrieval efficiency is initially determined to be unqualified, a secondary determination is made on whether the information retrieval efficiency is qualified based on the historical retrieval evaluation, or the reason why the information retrieval efficiency is unqualified is determined based on the retrieval evaluation; The calculation module calculates the search evaluation S according to the number of clicks A and the total browsing time T collected by the collection module, and sets the search evaluation S=a×A0 / A+t×T / T0, where a is the click weight coefficient, t is the time weight coefficient, a+t=1, A0 is the preset number of clicks preset in the data analysis module, and T0 is the preset total browsing time preset in the data analysis module; The acquisition module acquires the historical search evaluation in the historical record, and the data analysis module determines whether the information retrieval efficiency is qualified according to the absolute value of the difference between the acquired historical search evaluation and the search evaluation, and adjusts the preset total browsing time to a corresponding value according to the difference between the historical search evaluation and the search evaluation when the information retrieval efficiency is determined to be qualified, or, When the information retrieval efficiency is judged to be unqualified, the reason for the unqualified information retrieval efficiency is determined based on the retrieval evaluation; When the data analysis module determines that the preset total browsing time should be adjusted to a corresponding value according to the difference between the historical search evaluation and the search evaluation, the difference between the historical search evaluation and the search evaluation is recorded as a primary difference, and a plurality of correction methods for the preset total browsing time are provided based on the primary difference, and the correction range of each correction method for the preset total browsing time is different; When determining the reason why the information retrieval efficiency is unqualified based on the retrieval evaluation, the data analysis module determines the reason why the information retrieval efficiency is unqualified based on the ratio of the retrieval evaluation to a second preset retrieval evaluation preset in the data analysis module, or makes a secondary determination on the reason why the information retrieval efficiency is unqualified based on the click frequency, and the reasons include: unreasonable information field screening and a small range of information retrieval keywords.

2. The information intelligent classification and retrieval system for archive management according to claim 1 is characterized in that: When the data analysis module makes a secondary determination on the reasons why the information retrieval efficiency is unqualified according to the click frequency, the reasons for determining that the information retrieval efficiency is unqualified according to the click frequency include: unreasonable information field screening and a small range of information retrieval keywords.

3. The information intelligent classification and retrieval system for archive management according to claim 2 is characterized in that: When the data analysis module determines that the reason for the unqualified information retrieval efficiency is unreasonable information field screening, it determines whether the keyword meets the prompt standard according to the usage frequency of a single keyword in the current search result.

4. The information intelligent classification and retrieval system for archive management according to claim 3 is characterized in that: The data analysis module screens out the keywords currently input for retrieval when determining that the keywords meet the prompt standard, and sends the keywords to the display module when the screening is completed.

5. The information intelligent classification and retrieval system for archive management according to claim 4 is characterized in that: When the data analysis module determines that the reason for the unqualified information retrieval efficiency is that the information retrieval keyword range is small, it determines whether the information block meets the retrieval criteria based on the click frequency of the information block containing the keyword in the historical record, and adds the information block to the retrieval results when it is determined that the information block meets the retrieval criteria.

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