Intelligent retrieval system of digital medical knowledge base

Abstract

The invention discloses an intelligent retrieval system of a digital medical knowledge base, and relates to the field of intelligent retrieval, according to the intelligent retrieval system, authority information of search interfaces and user use information are comprehensively analyzed to obtain recommended values of the search interfaces, when a user performs retrieval, the search interfaces are arranged from top to bottom according to the recommended values, and the recommended values are stored in the search interfaces; the search accuracy is improved, and the user stickiness is increased; by deleting and adding the database regularly, the memory of the database is released, and meanwhile, it is ensured that the user can retrieve the latest medical achievements; through comprehensive analysis of the customer service, the customer service can be reasonably allocated to the user, and the selection right is handed over to the user in the final selection link, so that the satisfaction degree of the user is improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent retrieval systems, and in particular to an intelligent retrieval system for a digital medical knowledge base. Background Art

[0002] With the widespread application of information technology in the medical field, medical data has shown explosive growth, including electronic medical records, medical images, test reports, clinical guidelines, medical literature and other types of data. These data contain rich medical knowledge and clinical experience, but due to the huge amount of data and the fact that they are scattered in different systems and departments, the retrieval quality of traditional retrieval methods cannot be guaranteed, and users cannot distinguish between good and bad quality, which may cause users to receive wrong medical information and threaten their lives. In addition, the existing retrieval system has a low retrieval accuracy rate, which easily causes users to repeat the search many times, resulting in a decrease in user satisfaction; Therefore, an intelligent retrieval system for digital medical knowledge base is introduced. Summary of the invention

[0003] In view of this, the present invention provides an intelligent retrieval system for a digital medical knowledge base to solve the problems raised by the above-mentioned background technology.

[0004] The purpose of the present invention can be achieved through the following technical solutions: An intelligent retrieval system for a digital medical knowledge base, comprising: Data acquisition module: obtains authoritative information and user usage information of the search interface; authoritative information includes: search interface domain name weight, cited authors and the number of their documents, and the number of citations of the search interface; user usage information includes: user ratings of the search interface, user browsing time at each level, and user forwarding times; and sends the authoritative information and user usage information of the search interface to the search interface evaluation module; Search interface evaluation module: obtains the search interface authority value and user usage value through analysis of the interface authority information and user usage information respectively; then obtains the search interface recommendation value through comprehensive analysis of the search interface authority value and user usage value; Database update module: set the update time interval during the operation of the intelligent retrieval system, and delete and add the search interface in the medical knowledge base when the update time interval is reached; User interaction module: Users can issue search instructions to the intelligent search system through a variety of interactive methods to obtain the information they need; Interactive interface setting module: based on the recommended values ​​of each search interface, when the user issues a search command, the matched search interfaces are arranged in order from top to bottom according to the size of the corresponding recommended values; Manual customer service module: It is triggered when a user performs the same search command multiple times in a short period of time. The user can freely choose whether to access manual customer service.

[0005] In some embodiments, the authority value of the search interface is obtained, specifically: S1: Get the authoritative score of each author in the search interface, as follows: S1-1: Get the authors of each cited document in the search interface, get the number of papers published by each author in each journal, and get the impact factor of each journal from the journal citation report, recorded as , i=1,2...x, x is the total number of journals; the number of papers published by each author in each journal is , j=1, 2...n, n is the total number of authors cited in the current search interface, and the impact factor of each journal is obtained and the number of papers published by each author in the corresponding journal Substituting into the formula: Thus, we can get the journal score of each author. ; S1-2: Get the award type and corresponding number of awards of each author in the search interface. The award types are divided into: international, national and provincial awards; preset the weight impact factor corresponding to each award type, multiply the number of awards of each type by the weight factor of the corresponding award type, and then add them up to get the award score of each author ; S1-3: Get the H index of each author in the search interface and record it as the impact score , preset journal scores for each author , winning score And the impact score The corresponding weighted impact factor is the journal score of each author. , winning score And the impact score The author's authority index is obtained by multiplying the author's weighted impact factor and summing them up. ; S2: The authority index of each author in the search interface Multiply it by the number of works of the corresponding author, and then add them up to get the comprehensive literature score WXP on the search interface; S3: Preset the weight impact factors corresponding to the search interface domain name weight, the number of citations of the search interface and the comprehensive literature score WXP of the search interface. Multiply the search interface domain name weight, the number of citations of the search interface and the comprehensive literature score WXP of the search interface with their respective corresponding weight impact factors and sum them up. The result is used as the authority value ZHP of the search interface.

[0006] In some embodiments, obtaining the user usage value of the search interface is specifically: Taking a single user's single use of the intelligent retrieval system as the analysis interval, statistically analyzing the browsing time of a single user at each level in the search interface within the interval, presetting each group of time intervals corresponding to the browsing time, and presetting each group of scores corresponding to each time interval of each level based on the different levels; matching the time intervals corresponding to the browsing time of the user at each level, thereby obtaining the scores corresponding to the browsing time of the user at each level, and accumulating the scores corresponding to the browsing time of the user at each level, thereby obtaining the user's time usage score SC; Obtain each user's rating value and rating time for the search interface, subtract each user's rating time from the current time to obtain each user's rating interval, preset each group of rating interval time intervals corresponding to each group of credibility indicators, match each user's rating interval time interval corresponding to each user's rating interval time, thereby obtaining each user's credibility indicator corresponding to the rating interval time, multiply each user's rating value for the search interface by the corresponding credibility indicator, thereby obtaining each user's search interface adjusted rating value, and take the average of all users' search interface adjusted rating values ​​as the adjusted rating JQ; The number of times the user forwards is marked as ZF, and the obtained duration usage score SC, adjustment score JQ and the number of times the user forwards ZF are normalized and entered into the formula: Thus, the user usage value YHY is obtained, where z1, z2 and z3 are the weight influence factors corresponding to the duration usage score SC, the weighted score JQ and the number of user forwarding times ZF respectively.

[0007] In some embodiments, the recommended value of the search interface is obtained, specifically: The obtained authority value ZHP and user usage value YHY of the search interface are normalized, and the corresponding weight influence factors of the authority value ZHP and user usage value YHY of the search interface are preset. The authority value ZHP and user usage value YHY of the search interface are multiplied by their respective preset weight influence factors and then summed up, and the result is used as the recommended value TJZ of the search interface.

[0008] In some embodiments, the search interface in the medical database is deleted, specifically: The search interfaces in the medical database are classified according to the disease type, which includes but is not limited to: cardiovascular and cerebrovascular diseases, pneumonia, colds, etc. A maintenance node is set during the operation of the medical database. When the maintenance node is reached, the m search interfaces with the smallest search interface recommendation value TJZ under various disease types are extracted, where m>5. The most recent use score and the most recent use time of each search interface are obtained, and the most recent use time of each search interface is subtracted from the current maintenance node time to obtain the stop use time SJ of each search interface. The user's most recent use score is marked as PF. The stop use time SJ of each search interface, the interface recommendation value TJZ, and the most recent use score PF are normalized and then entered into the formula: Thus, the deletion judgment index SCP of each search interface is obtained, where c1, c2 and c3 are the weight influence factors corresponding to the interface recommendation value TJZ, the most recent use score mark PF and the interface stop use time SJ respectively. The n search interfaces with the lowest deletion judgment index SCP under each disease type are selected for deletion operation. <n<m。

[0009] In some embodiments, the medical database is added by: When the maintenance node of the database is reached, a medical-related search interface that does not exist in the current medical knowledge base is obtained from the external resource library, a time update value is set, and the time difference between the obtained search interface and the current maintenance node is calculated. When the time difference is less than the time update value, the corresponding search interface is directly added to the current medical knowledge base; when the time difference is greater than the time update value, a search interface recommendation value threshold is preset, and the recommended value of the search interface whose time difference is greater than the time update value is calculated. The recommended value of the search interface corresponding to the time difference greater than the time update value is compared with the preset search interface recommendation value threshold. When the recommended value of the search interface corresponding to the time difference greater than the time update value is greater than the preset search interface recommendation value threshold, the corresponding search interface is added to the current medical knowledge base.

[0010] In some embodiments, selecting a suitable customer service staff for the user is as follows: Set time nodes in the preset time interval, obtain the number of customers received, problem solving rate and customer scores of each customer service staff at each time node, take the average score of each customer at each time node as the average score at the corresponding time node, preset the weight influence factors corresponding to the average score, number of customers received and problem solving rate, multiply the average score, number of customers received and problem solving rate at each time node by the preset weight influence factors respectively, and then sum them up, and the final result is taken as the customer comprehensive score KFP at the corresponding time node; Extract the four values ​​of the comprehensive customer service score KFP at each time node in the time interval, which are the value corresponding to the first time node, the value corresponding to the last time node, the maximum value and the minimum value; subtract the value corresponding to the first time node from the minimum value as the first analysis value W1; subtract the maximum value from the value corresponding to the last time node as the second analysis value W2; subtract the value corresponding to the first time node from the value corresponding to the last time node as the third analysis value W3, and substitute the first analysis value W1, the second analysis value W2 and the third analysis value W3 into the formula: Thus, the score correction value corresponding to each customer service is obtained, where s1, s2 and s3 are the weight influence factors corresponding to the first analysis value W1, the second analysis value W2 and the third analysis value W3 respectively; Take the average of the customer service comprehensive score KFP at each time node as the service score of the corresponding customer service, add the customer service score and the score correction value of the corresponding customer service, and thus obtain the corrected service score T2 of each customer service; When a user performs the same search command multiple times in a short period of time, customer service intervention is triggered, and the user can freely choose whether to access manual customer service; when the user chooses to access manual customer service, the number of people to be processed T1, the corrected service score T2 and the cumulative online time T3 of each online customer service are obtained, and the formula is used: Get the customer service reception index KFJ of each current online customer service, extract the top three customer service staff with the customer service reception index KFJ among the current online customer service staff, obtain the age, years of experience, number of people to be received, avatar and praise rate of the corresponding customer service staff, package them and send them to the user's interactive interface, and the user can choose which customer service staff to connect to.

[0011] Compared with the prior art, the present invention has the following beneficial effects: The present invention comprehensively analyzes the authority and usability of the search interface, thereby obtaining the recommended value of each search interface. When the user uses the search system to search, the search interface is arranged from top to bottom according to the size of the recommended value, thereby avoiding the time loss and health loss caused by the user receiving some messy information and information irrelevant to the disease, and increasing the reliability of the search effect. The present invention can ensure that users can retrieve the latest research results by regularly deleting and adding search interfaces in the database, thereby improving the timeliness of data update; by analyzing the deletion evaluation index of the search interface in the database, some useless search interfaces are reasonably deleted, thereby regularly releasing database memory, and avoiding the bad experience caused by users retrieving such irrelevant information; The present invention obtains the customer service reception index corresponding to each customer service through comprehensive analysis of customer services, selects the top three customer services with the customer service reception index, packages the relevant information together and sends it to the user's interactive interface, so that the user can independently choose which customer service to access, thereby improving user satisfaction and customer stickiness. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Further details, features and advantages of the present application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which: Figure 1 It is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0013] Several embodiments of the present application will be described in more detail below with reference to the accompanying drawings so that those skilled in the art can implement the present application. The present application can be embodied in many different forms and purposes and should not be limited to the embodiments described herein. These embodiments are provided to make the present application comprehensive and complete, and to fully convey the scope of the present application to those skilled in the art. The embodiments do not limit the present application.

[0014] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art to which this application belongs. It will be further understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the relevant art and / or the context of this specification, and will not be interpreted in an idealized or overly formal sense unless explicitly defined as such herein.

[0015] See also Figure 1 As shown, an intelligent retrieval system for a digital medical knowledge base includes: a data acquisition module, a search interface evaluation module, a database update module, a user interaction module, an interaction interface setting module, and a manual customer service module; Data acquisition module: obtains authoritative information and user usage information of the search interface; authoritative information includes: search interface domain name weight, cited authors and the number of their documents, and the number of citations of the search interface; user usage information includes: user ratings of the search interface, user browsing time at each level, and user forwarding times; and sends the authoritative information and user usage information of the search interface to the search interface evaluation module; Search interface evaluation module: obtains the search interface authority value and user usage value through analysis of the interface authority information and user usage information respectively; then obtains the search interface recommendation value through comprehensive analysis of the search interface authority value and user usage value; S1: Get the authoritative score of each author in the search interface, as follows: S1-1: Get the authors of each cited document in the search interface, get the number of papers published by each author in each journal, and get the impact factor of each journal from the journal citation report, recorded as , i=1,2...x, x is the total number of journals; the number of papers published by each author in each journal is , j=1, 2...n, n is the total number of authors cited in the current search interface, and the impact factor of each journal is obtained and the number of papers published by each author in the corresponding journal Substituting into the formula: Thus, we can get the journal score of each author. ; S1-2: Get the award type and corresponding number of awards of each author in the search interface. The award types are divided into: international, national and provincial awards; preset the weight impact factor corresponding to each award type, multiply the number of awards of each type by the weight factor of the corresponding award type, and then add them up to get the award score of each author ; Different weight factors are set for different award types, taking into account the different gold content of different types of awards, so that the award scores It can better reflect the award-winning situation of the corresponding author; S1-3: Get the H index of each author in the search interface and record it as the impact score , preset journal scores for each author , winning score And the impact score The corresponding weighted impact factor is the journal score of each author. , winning score And the impact score The author's authority index is obtained by multiplying the author's weighted impact factor and summing them up. ; By calculating the authority index of each author , which can evaluate the authority of each author in the medical field in the search interface, the authority index The higher the score, the more authoritative the author is in the medical field and the more valuable his / her work is. S2: The authority index of each author in the search interface Multiply it by the number of works of the corresponding author, and then add them up to get the comprehensive literature score WXP on the search interface; S3: Preset the weight impact factor corresponding to the search interface domain name weight, the number of citations of the search interface, and the comprehensive score of the literature WXP of the search interface. Multiply the search interface domain name weight, the number of citations of the search interface, and the comprehensive score of the literature WXP of the search interface by their corresponding weight impact factors and sum them up. The result is used as the authority value ZHP of the search interface. Comprehensively evaluating the authority of a search interface from three different dimensions makes the results more reliable and avoids the contingency caused by a single factor; Taking a single user's single use of the intelligent retrieval system as the analysis interval, the browsing time of a single user at each level in the search interface within the analysis interval is statistically analyzed, and each group of time intervals corresponding to the browsing time is preset. Based on the different levels, each time interval at each level is preset to correspond to each group of scores; for example, for a browsing time interval of 3-5 minutes, the score set by the user at the first level is 5, the score set at the second level is 8, and the score set at the third level is 13; Match the duration intervals corresponding to the user's browsing duration at each level, thereby obtaining the scores corresponding to the user's browsing duration at each level, and add up the scores corresponding to the user's browsing duration at each level, thereby obtaining the user's duration usage score SC; The higher the number of levels a user browses, the longer they stay on the interface with a higher number of levels, which means that the information provided by the search interface is more accurate. For the same time interval, different scores are set at different levels, taking into account the impact of the level factor on the search interface, making the analysis of browsing time more accurate; Obtain each user's rating value and rating time for the search interface, subtract each user's rating time from the current time to obtain each user's rating interval, preset each group of rating interval time intervals corresponding to each group of credibility indicators, match each user's rating interval time interval corresponding to each user's rating interval time, thereby obtaining each user's credibility indicator corresponding to the rating interval time, multiply each user's rating value for the search interface by the corresponding credibility indicator, thereby obtaining each user's search interface adjusted rating value, and take the average of all users' search interface adjusted rating values ​​as the adjusted rating JQ; The search interface will continue to improve. The previous ratings cannot fully represent the current situation. Different credibility indicators are set for each group of rating intervals. The impact of time factors on the rating value is taken into account, so that the adjusted ratings can better reflect the user's rating of the interface. The number of times the user forwards is marked as ZF, and the obtained duration usage score SC, adjustment score JQ and the number of times the user forwards ZF are normalized and entered into the formula: Thus, the user usage value YHY is obtained, where z1, z2 and z3 are the weighted influence factors corresponding to the duration usage score SC, the weighted score JQ and the number of user forwarding times ZF respectively; The obtained authority value ZHP and user usage value YHY of the search interface are normalized, and the weight influence factors corresponding to the authority value ZHP and user usage value YHY of the search interface are preset. The authority value ZHP and user usage value YHY of the search interface are multiplied by their respective preset weight influence factors and then summed, and the result is taken as the recommended value TJZ of the search interface; The more authoritative a search interface is, the better it is. Users’ feelings about the search interface are also an important consideration in evaluating the search interface. By comprehensively considering the authority and user usage value of the search interface and setting weight influence factors to obtain the recommended value of the search interface, more users can be taken care of. Database update module: set the update time interval during the operation of the intelligent retrieval system, and delete and add the search interface in the medical knowledge base when the update time interval is reached; The search interfaces in the medical database are classified according to the disease type, which includes but is not limited to: cardiovascular and cerebrovascular diseases, pneumonia, colds, etc. A maintenance node is set during the operation of the medical database. When the maintenance node is reached, the m search interfaces with the smallest search interface recommendation value TJZ under various disease types are extracted, where m>5. The most recent use score and the most recent use time of each search interface are obtained, and the most recent use time of each search interface is subtracted from the current maintenance node time to obtain the stop use time SJ of each search interface. The user's most recent use score is marked as PF. The stop use time SJ of each search interface, the interface recommendation value TJZ, and the most recent use score PF are normalized and then entered into the formula: Thus, the deletion judgment index SCP of each search interface is obtained, where c1, c2 and c3 are the weight influence factors corresponding to the interface recommendation value TJZ, the most recent use score mark PF and the interface stop use time SJ respectively. The n search interfaces with the lowest deletion judgment index SCP under each disease type are selected for deletion operation. <n<m; By regularly deleting useless search interfaces in the database, database memory can be released to avoid database explosion; When the maintenance node of the database is reached, a medical-related search interface that does not exist in the current medical knowledge base is obtained in the external resource library, a time update value is set, and the time difference between the obtained search interface and the current maintenance node is calculated. When the time difference is less than the time update value, the corresponding search interface is directly added to the current medical knowledge base; when the time difference is greater than the time update value, a search interface recommendation value threshold is preset, and the recommended value of the search interface whose time difference is greater than the time update value is calculated, and the recommended value of the search interface corresponding to the time difference greater than the time update value is compared with the preset search interface recommendation value threshold. When the recommended value of the search interface corresponding to the time difference greater than the time update value is greater than the preset search interface recommendation value threshold, the corresponding search interface is added to the current medical knowledge base; By increasing the content of the medical knowledge base, users can receive the latest medical knowledge, improving the timeliness of information updates; User interaction module: Users can issue search instructions to the intelligent search system through a variety of interactive methods to obtain the information they need; Interactive interface setting module: based on the recommended values ​​of each search interface, when the user issues a search command, the matched search interfaces are arranged in order from top to bottom according to the size of the corresponding recommended values; Manual customer service module: It is triggered when a user performs the same search command multiple times in a short period of time. The user can freely choose whether to access manual customer service; Set time nodes in the preset time interval, obtain the number of customers received, problem solving rate and customer scores of each customer service staff at each time node, take the average score of each customer at each time node as the average score at the corresponding time node, preset the weight influence factors corresponding to the average score, number of customers received and problem solving rate, multiply the average score, number of customers received and problem solving rate at each time node by the preset weight influence factors respectively, and then sum them up, and the final result is taken as the customer comprehensive score KFP at the corresponding time node; Judging the excellence of customer service from multiple dimensions, the larger the comprehensive customer service score KFP is, the higher the customer service ability is; Extract the four values ​​of the comprehensive customer service score KFP at each time node in the time interval, which are the value corresponding to the first time node, the value corresponding to the last time node, the maximum value and the minimum value; subtract the value corresponding to the first time node from the minimum value as the first analysis value W1; subtract the maximum value from the value corresponding to the last time node as the second analysis value W2; subtract the value corresponding to the first time node from the value corresponding to the last time node as the third analysis value W3, and substitute the first analysis value W1, the second analysis value W2 and the third analysis value W3 into the formula: Thus, the score correction value corresponding to each customer service is obtained, where s1, s2 and s3 are the weight influence factors corresponding to the first analysis value W1, the second analysis value W2 and the third analysis value W3 respectively; Take the average of the customer service comprehensive score KFP at each time node as the service score of the corresponding customer service, add the customer service score and the score correction value of the corresponding customer service, and thus obtain the corrected service score T2 of each customer service; When a user performs the same search command multiple times in a short period of time, customer service intervention is triggered, and the user can freely choose whether to access manual customer service; when the user chooses to access manual customer service, the number of people to be processed T1, the corrected service score T2 and the cumulative online time T3 of each online customer service are obtained, and the formula is used: Get the customer service reception index KFJ of each current online customer service, extract the top three customers with the customer service reception index KFJ among the current online customer service, obtain the age, years of experience, number of people to be received, avatar and praise rate of the corresponding customer service, package and send to the user's interactive interface, and the user can choose which customer service to connect to; Through comprehensive analysis of the number of people to be processed T1, the revised service score T2, and the cumulative online time T3 of each customer service, it is possible to reasonably allocate customer service to users who are currently accessing the customer service channel, thus avoiding users from waiting too long, and giving users the right to choose which customer service to serve, thereby improving user satisfaction. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An intelligent retrieval system for a digital medical knowledge base, characterized in that: include: Data acquisition module: obtain authoritative information and user usage information of the search interface; Authoritative information includes: search interface domain name weight, cited authors and the number of their documents, and the number of citations of the search interface; user usage information includes: user ratings of the search interface, user browsing time at each level, and user forwarding times; and the authoritative information and user usage information of the search interface are sent to the search interface evaluation module; Search interface evaluation module: obtains the search interface authority value and user usage value through analysis of the interface authority information and user usage information respectively; then obtains the search interface recommendation value through comprehensive analysis of the search interface authority value and user usage value; Database update module: set the update time interval during the operation of the intelligent retrieval system, and delete and add the search interface in the medical knowledge base when the update time interval is reached; User interaction module: Users can issue search instructions to the intelligent search system through a variety of interactive methods to obtain the information they need; Interactive interface setting module: based on the recommended values ​​of each search interface, when the user issues a search command, the matched search interfaces are arranged in order from top to bottom according to the size of the corresponding recommended values; Manual customer service module: It is triggered when a user performs the same search command multiple times in a short period of time. The user can freely choose whether to access manual customer service.

2. According to claim 1, the intelligent retrieval system for a digital medical knowledge base is characterized in that: Get the authority value of the search interface, specifically: S1: Get the authoritative score of each author in the search interface, as follows: S1-1: Get the authors of each cited document in the search interface, the number of papers published by each author in each journal, and the impact factor of each journal, recorded as , i=1,2...x, x is the total number of journals; the number of papers published by each author in each journal is , j=1, 2...n, n is the total number of authors cited in the current search interface, and the impact factor of each journal is obtained and the number of papers published by each author in the corresponding journal Substituting into the formula: Thus, we can get the journal score of each author. ; S1-2: Get the award type and corresponding number of awards of each author in the search interface. The award types are divided into: international, national and provincial awards; preset the weight impact factor corresponding to each award type, multiply the number of awards of each type by the weight factor of the corresponding award type, and then add them up to get the award score of each author ; S1-3: Get the H index of each author in the search interface and record it as the impact score , preset journal scores for each author , winning score And the impact score The corresponding weighted impact factor is the journal score of each author. , winning score And the impact score The author's authority index is obtained by multiplying the author's weighted impact factor and summing them up. ; S2: The authority index of each author in the search interface Multiply it by the number of works of the corresponding author, and then add them up to get the comprehensive literature score WXP on the search interface; S3: Preset the weight impact factors corresponding to the search interface domain name weight, the number of citations of the search interface and the comprehensive literature score WXP of the search interface. Multiply the search interface domain name weight, the number of citations of the search interface and the comprehensive literature score WXP of the search interface with their respective corresponding weight impact factors and sum them up. The result is used as the authority value ZHP of the search interface.

3. The intelligent retrieval system for a digital medical knowledge base according to claim 2, characterized in that: Get the user usage value of the search interface, specifically: Taking a single user's single use of the intelligent retrieval system as the analysis interval, statistically analyzing the browsing time of a single user at each level in the search interface within the interval, presetting each group of time intervals corresponding to the browsing time, and presetting each group of scores corresponding to each time interval of each level based on the different levels; matching the time intervals corresponding to the browsing time of the user at each level, thereby obtaining the scores corresponding to the browsing time of the user at each level, and accumulating the scores corresponding to the browsing time of the user at each level, thereby obtaining the user's time usage score SC; Obtain each user's rating value and rating time for the search interface, subtract each user's rating time from the current time to obtain each user's rating interval, preset each group of rating interval time intervals corresponding to each group of credibility indicators, match each user's rating interval time interval corresponding to each user's rating interval time, thereby obtaining each user's credibility indicator corresponding to the rating interval time, multiply each user's rating value for the search interface by the corresponding credibility indicator, thereby obtaining each user's search interface adjusted rating value, and take the average of all users' search interface adjusted rating values ​​as the adjusted rating JQ; The number of times the user forwards is marked as ZF, and the obtained duration is normalized using the score SC, the adjustment score JQ, and the number of times the user forwards ZF and then entered into the formula: Thus, the user usage value YHY is obtained, where z1, z2 and z3 are the weight influence factors corresponding to the duration usage score SC, the weighted score JQ and the number of user forwarding times ZF respectively.

4. The intelligent retrieval system for a digital medical knowledge base according to claim 3, characterized in that: Get the recommended values ​​for the search interface, specifically: The obtained authority value ZHP and user usage value YHY of the search interface are normalized, and the corresponding weight influence factors of the authority value ZHP and user usage value YHY of the search interface are preset. The authority value ZHP and user usage value YHY of the search interface are multiplied by their respective preset weight influence factors and then summed up, and the result is used as the recommended value TJZ of the search interface.

5. The intelligent retrieval system for a digital medical knowledge base according to claim 4, characterized in that: Delete the search interface in the medical database, specifically: The search interfaces in the medical database are classified according to the disease type. When the update time interval of the database is reached, the m search interfaces with the smallest search interface recommendation value TJZ under various disease types are extracted, where m>5. The most recent use score and the most recent use time of each search interface are obtained. The most recent use time of each search interface is subtracted from the current maintenance node time to obtain the stop use time SJ of each search interface. The user's most recent use score is marked as PF. The stop use time SJ of each search interface, the interface recommendation value TJZ, and the most recent use score PF are normalized and entered into the formula: Thus, the deletion judgment index SCP of each search interface is obtained, where c1, c2 and c3 are the weight influence factors corresponding to the interface recommendation value TJZ, the most recent use score mark PF and the interface stop use time SJ respectively. The n search interfaces with the lowest deletion judgment index SCP under each disease type are selected for deletion operation. <n<m。 6. The intelligent retrieval system for a digital medical knowledge base according to claim 5, characterized in that: Perform additional operations on the medical database, specifically: When the update time interval of the database is reached, a medical-related search interface that does not exist in the current medical knowledge base is obtained from the external resource library, a time update value is set, and the time difference between the obtained search interface and the current maintenance node is calculated. When the time difference is less than the time update value, the corresponding search interface is directly added to the current medical knowledge base; When the time difference is greater than the time update value, a search interface recommendation value threshold is preset, the recommended value of the search interface where the time difference is greater than the time update value is calculated, and the recommended value of the search interface corresponding to the time difference being greater than the time update value is compared with the preset search interface recommendation value threshold; when the recommended value of the search interface corresponding to the time difference being greater than the time update value is greater than the preset search interface recommendation value threshold, the corresponding search interface is added to the current medical knowledge base.

7. The intelligent retrieval system for a digital medical knowledge base according to claim 6, characterized in that: Select appropriate customer service personnel for users, specifically: Set time nodes in the preset time interval, obtain the number of customers received, problem solving rate and customer scores of each customer service staff at each time node, take the average score of each customer at each time node as the average score at the corresponding time node, preset the weight influence factors corresponding to the average score, number of customers received and problem solving rate, multiply the average score, number of customers received and problem solving rate at each time node by the preset weight influence factors respectively, and then sum them up, and the final result is taken as the customer comprehensive score KFP at the corresponding time node; Extract the four values ​​of the comprehensive customer service score KFP at each time node in the time interval, which are the value corresponding to the first time node, the value corresponding to the last time node, the maximum value and the minimum value; subtract the value corresponding to the first time node from the minimum value as the first analysis value W1; subtract the maximum value from the value corresponding to the last time node as the second analysis value W2; subtract the value corresponding to the first time node from the value corresponding to the last time node as the third analysis value W3, and substitute the first analysis value W1, the second analysis value W2 and the third analysis value W3 into the formula: Thus, the score correction value corresponding to each customer service is obtained, where s1, s2 and s3 are the weight influence factors corresponding to the first analysis value W1, the second analysis value W2 and the third analysis value W3 respectively; Take the average of the customer service comprehensive score KFP at each time node as the service score of the corresponding customer service, add the customer service score and the score correction value of the corresponding customer service, and thus obtain the corrected service score T2 of each customer service; When the user chooses to access manual customer service, the number of people to be processed T1, the corrected service score T2, and the cumulative online time T3 of each online customer service are obtained, using the formula: Get the customer service reception index KFJ of each current online customer service, extract the top three customer service staff with the customer service reception index KFJ among the current online customer service staff, obtain the age, years of experience, number of people to be received, avatar and praise rate of the corresponding customer service staff, package them and send them to the user's interactive interface, and the user can choose which customer service staff to connect to.

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