CN111159216A

CN111159216A - Method and system for searching doctor information in inquiry platform

Info

Publication number: CN111159216A
Application number: CN201911286727.XA
Authority: CN
Inventors: 杨健; 袁孟全
Original assignee: Guiyang Longmaster Information and Technology Co ltd
Current assignee: Guiyang Longmaster Information and Technology Co ltd
Priority date: 2019-12-14
Filing date: 2019-12-14
Publication date: 2020-05-15

Abstract

According to the method and the system for searching the doctor information in the inquiry platform, the json string is obtained according to the keywords input by the user; writing a first DQL statement according to the json string; performing word segmentation search according to the first DQL statement to obtain a keyword search result; sorting the keyword search results according to a preset scoring rule to obtain keyword sorting results; and outputting a preset number of search results from the keyword sequencing results to a user, realizing that the related content of the keywords can be searched out in real time, accurately and in word segmentation, and outputting the related content according to the keyword relevance in sequence. On the basis of not changing the original architecture, the development of writing large-length SQL sentences by developers is reduced through the search engine.

Description

Method and system for searching doctor information in inquiry platform

Technical Field

The application relates to the technical field of medical health, in particular to a method and a system for searching doctor information in an inquiry platform.

Background

Due to business requirements, the doctor workstation needs to search out relevant information of a doctor in real time, accurately and in word segmentation according to the name of the doctor or the name of a disease, and the relevant information is directly obtained from a MYSQL database by writing SQL sentences in the original method. However, the above method cannot meet the requirement, because the MYSQL service, under the condition that no index is established in the name field or the disease field, the query speed is slower and slower along with the accumulation of data volume, and the near-real-time effect cannot be achieved. Although MYSQL can realize accurate query through the '%' keyword, the word segmentation result cannot be realized.

Disclosure of Invention

The application provides a method and a system for searching doctor information in an inquiry platform, which aim to solve the problem that the existing user cannot accurately search the doctor information.

In a first aspect, to achieve the above object, the present application provides a method for searching doctor information in an inquiry platform, the method comprising:

acquiring a json string according to a keyword input by a user;

writing a first DQL statement according to the json string;

performing word segmentation search according to the first DQL statement to obtain a keyword search result;

sorting the keyword search results according to a preset scoring rule to obtain keyword sorting results;

and outputting a preset number of search results from the keyword sorting results to the user.

Further, before writing the json string as the first DQL statement, the method further includes:

and checking the validity of the json string.

Further, the performing word segmentation search according to the first DQL statement to obtain a keyword search result includes:

inquiring all information with keyword prefixes;

inquiring all information with keyword phrases;

all the information contained in the keywords is queried.

Further, the method for searching doctor information in the inquiry platform further comprises the following steps:

and acquiring doctor information data from the MYSQL database according to a preset period.

Further, the acquiring of doctor information data from the MYSQL database according to the preset period includes:

assembling an sql statement of the query;

acquiring doctor information data from a MYSQL database through the sql statement;

assembling a second DQL statement which can be identified by the ES server;

and importing the doctor information data into the ES server through the second DQL statement.

In a second aspect, the application further provides a system for searching doctor information in an inquiry platform, wherein the system comprises a WEB server, a MYSQL database and an ES server; the ES server includes:

the acquiring unit is used for acquiring a json string according to a keyword input by a user;

the search unit is used for writing a first DQL statement according to the json string;

and the conveying unit is used for outputting a preset number of search results from the keyword sorting results to the user.

Further, the obtaining unit is further configured to:

and checking the validity of the json string.

Further, the search unit is configured to:

inquiring all information with keyword prefixes;

inquiring all information with keyword phrases;

all the information contained in the keywords is queried.

Further, the system for searching doctor information in the interrogation platform further comprises a data synchronization service unit, which is used for:

Further, the data synchronization service unit is configured to:

assembling an sql statement of the query;

assembling a second DQL statement which can be identified by the ES server;

In a third aspect, to achieve the above object, the present application provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of the method for student information search in any of the interrogation platforms of the first aspect.

In a fourth aspect, to achieve the above object, the present application provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the steps of the method for searching student information in the interrogation platform of any one of the first aspect.

According to the technical scheme, the method and the system for searching the doctor information in the inquiry platform provided by the embodiment of the application acquire the json string according to the keywords input by the user; writing a first DQL statement according to the json string; performing word segmentation search according to the first DQL statement to obtain a keyword search result; sorting the keyword search results according to a preset scoring rule to obtain keyword sorting results; and outputting a preset number of search results from the keyword sequencing results to a user, realizing that the related content of the keywords can be searched out in real time, accurately and in word segmentation, and outputting the related content according to the keyword relevance in sequence. On the basis of not changing the original architecture, the development of writing large-length SQL sentences by developers is reduced through the search engine.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.

Drawings

In order to more clearly describe the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive exercise.

Fig. 1 is a schematic flowchart of a method for searching doctor information in an interrogation platform according to an embodiment of the present application;

FIG. 2 is a schematic diagram illustrating a timing sequence for a search request according to an embodiment of the present disclosure;

FIG. 3 is a flowchart of a data import procedure according to an embodiment of the present application;

FIG. 4 is a schematic diagram of stored data provided by an embodiment of the present application;

fig. 5 is a schematic structural diagram of a system for searching doctor information in an inquiry platform according to an embodiment of the present application;

fig. 6 is a schematic structural diagram of an ES server according to an embodiment of the present application.

Detailed Description

The features and advantages of the present application will become more apparent and appreciated from the following detailed description of the application.

The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

In the description of the present application, it should be noted that the terms "upper", "lower", "inner", "outer", "front", "rear", "left" and "right" and the like indicate orientations or positional relationships based on operational states of the present application, and are only used for convenience of description and simplification of description, but do not indicate or imply that the system or element being referred to must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present application. Furthermore, the terms "first," "second," "third," and "fourth" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.

If a user directly queries the MYSQL database through the doctor name or the disease name, the related information of the doctor can be rapidly and accurately queried, on the premise that indexes need to be built in the doctor name field and the disease field, but the doctor name and the disease name are long in content, the occupied space is larger along with the increase of the data volume, the common MYSQL building indexes in the field are rare, even if the indexes are built in the field, the related information of the doctor is respectively stored in different tables, and as a result, when a SQL sentence is queried and written, LEFT JOIN tables are needed, and the query efficiency is obviously low. Also MYQL is a function that does not support word segmentation, such as: the disease requiring the keyword "coronary heart disease" is searched, according to the common writing method of MYSQL, "% coronary heart disease" is used to search all the related information with the whole word "coronary heart disease", but the information of "coronary heart disease", and "disease" cannot be searched. The following problems need to be solved: reducing the writing of large-space query SQL sentences by developers; obtaining a result according to the near real-time query of the keywords and outputting the result according to the degree of the keyword relevance in a sequence; and supporting the keyword word segmentation function.

In order to solve the above problems, the present application provides a method and a system for searching doctor information in an inquiry platform, and the following describes a specific embodiment of the present application in detail with reference to the accompanying drawings.

Fig. 1 is a schematic flowchart of a method for searching for doctor information in an interrogation platform according to an embodiment of the present application, and as shown in fig. 1, the method includes steps S1001 to S1005.

S1001: and acquiring a json string according to the keywords input by the user.

For example, the user inputs or selects the query with the keyword "korea doctor", "coronary heart disease", "chief physician", "cardiology", "qian south people's hospital" through the front-end APP, and the user-end APP forms the corresponding json string according to the preset protocol, such as

http://10.254.33.109/client _ api/? json { "op _ type":200001, "real _ name": korean doctor, "illiness": coronary heart disease, "" professional ": main doctor," "department": cardiology, "" hospital, "and" qian nan state people hospital.

And transmitting the grouped json strings to a PHP service of a WEB server side, wherein the request format is ip, and port/client _ api/json is json strings, and the PHP service checks the validity of the json strings after receiving the request. And checking the validity of the parameters client _ api and json in sequence, and if the parameters client _ api and json are normal, taking out the value of the op _ type field in the json string, wherein if the value of the op _ type field is equal to 200001, a query request for the keyword is represented.

S1002: and writing a first DQL statement according to the json string.

S1003: and performing word segmentation search according to the first DQL statement to obtain a keyword search result.

Performing word segmentation search according to the first DQL statement to obtain a keyword search result, including:

inquiring all information with keyword prefixes;

inquiring all information with keyword phrases;

all the information contained in the keywords is queried.

S1004: and sorting the keyword search results according to a preset scoring rule to obtain a keyword sorting result.

S1005: and outputting a preset number of search results from the keyword sorting results to the user.

In specific implementation, if the json string is valid, a first DQL sentence which can be identified by an ElasticSearch search engine (ES server) is written for key sub-query, the ElasticSearch search engine performs word segmentation search query according to keywords after receiving a request, performs correlation scoring on the keywords, performs scoring according to a DQL preset scoring rule, returns the score to a PHP service according to the score, and forwards a search result to a front-end APP after the PHP service receives feedback of the ElasticSearch search engine, and then displays the search result on an interface.

Specifically, a first DQL statement recognizable by the ElasticSearch search engine is written as follows:

in the first DQL statement, the three keywords that mainly have word segmentation function are "match _ phrase _ prefix", "match _ phrase", and "match", and the specific functions are as follows:

match _ phrase _ prefix: inquiring all information with the keyword prefixes, such as the information of the Korean doctor in the example, inquiring information of the Korean doctor, the information of the Korean doctor and the information of the Korean doctor, and the like;

match _ phrase: inquiring all information with keyword phrases, such as coronary heart disease in the example, inquiring information such as coronary heart disease, coronary heart disease information, heart-brain coronary heart disease and the like;

match: inquiring all the information contained in the keywords, such as "principal physician" in the example, inquiring the information of "principal physician", "principal", "physician", "principal physician", etc.; which page from and how many keywords in the sentence represent the first 100 pieces of information returned from the result of the query; the keyword "source" represents a scoring rule; the keywords "query", "cool", "script" are DQL usage formats supported by the ElasticSearch service.

And (3) grading rules: score ═ score + reception _ num-host _ sort

Specifically, the method comprises the following steps:

score: a score representing a query for relevant documents by keywords, the higher the score, the greater the relevance, and the further forward the ranking output;

sclore: the ElasticSearch scores relevant documents of the query keywords, the higher the score is, the greater the relevance is, and the used scoring calculation formula is called a practical scoring function:

score(q,d)＝queryNorm(q)·coord(q,d)·∑(tf(tind)·idf(t)²·t.getBoost()·norm(t,d))(t in q)

score (q, d) is the relevance score of document d to query q.

queryNorm (q) is the query normalization factor.

coord (q, d) is a co-ordination factor.

Σ () (t in q) looks up the weighted sum of each word t in q for document d.

tf (t in d) is the word frequency of the word t in the document d.

idf (t) is the inverse document frequency of the word t.

Getboost () is the boost used in the query.

norm (t, d) is the sum of the field length normalization value, and the index time field layer boost (if present).

hospital _ sort: hospital ranks, stored as small to large numbers, which are the home hospital's repeat rank, with smaller numbers going forward, and if the hospital does not have a rank, the default setting is 9999999 when deriving the hospital rank field from MYSQL;

reception _ num: the times of doctor's receiving treatment are accumulated along with the number of doctor's receiving treatment cases, and the more times of receiving treatment, the more advanced the physician is.

Fig. 2 is a schematic diagram of a time sequence flow of a request search provided in an embodiment of the present application, and as shown in fig. 2, the method can retrieve related contents of keywords in near real time, accurately and in terms of words, and can output the related contents in an order of the keyword relevance, and by using the search engine, writing of large-length SQL statements by developers is reduced.

s1006: and acquiring doctor information data from the MYSQL database according to a preset period.

The MYSQL database stores doctor information which is respectively stored in fields of different tables, and the original direct query of all doctor information in the MYSQL database needs to be combined with multiple tables for query, so that the query efficiency is low; the invention leads all doctor information in the MYSQL database into the ElasticSearch search engine at one time through a data synchronization service program, can be understood as information stored in a plurality of tables in the MYSQL database, and is stored by using an index table after being synchronized to the ElasticSearch search engine. When inquiring, only the index is needed to inquire to obtain all the information of the keyword.

In specific implementation, as shown in fig. 3, the doctor information data is imported from the MYSQL database to the ElasticSearch engine according to a preset cycle through a data synchronization service program, specifically:

the synchronous service program assembles the sql statement of the query;

acquiring doctor information data from a MYSQL database through the sql statement: the synchronous service program queries and acquires data through the sql statement, and the MYSQL database replies the queried data;

the synchronous program assembles a second DQL statement which can be identified by the ES server;

importing the doctor information data into the ES server through the second DQL statement;

the ES server replies with the import result.

For example, as shown in FIG. 4, a physician index table is created in the ElasticSearch search engine, such as: t _ sector _ info, fields stored in the index table are (doctor ID, name, hospital, department, time of visit, hospital rank, cost.)

The create statement is as follows:

using sql statement to query the MYSQL database for the data corresponding to index table t _ sector _ info, the sql statement is as follows:

FROM doctor information correlation table WHERE vector _ ID >0 this statement represents a query for all doctor information for which doctor ID is greater than 0.

And starting a synchronization service program to import doctor information data from the MYSQL database into the ElasticSearch search engine, and triggering to initiate data synchronization every five minutes by the synchronization service program, so that the latest data can be conveniently inquired after the doctor information is updated. And assembling a query statement sql, initiating data query to acquire source data, returning data to a synchronous service program by the MYSQL database, and assembling the data into a second DQL (DataQueryLanguage) statement identified by the ElasticSarch search engine for data import.

For example, the second DQL statement for importing a piece of doctor information to the ElasticSearch engine is as follows:

POST 192.168.190.132:9200/t_doctor_info/_bulk

{"index":{"_index":"doctor_info","_type":"t_doctor_info","_id":10001}}

{

"doctor_id":10001,

"real _ name": physician ",

"sector _ level": the "intracardiac attending physician",

"reception_price":20,

"reception_dt":"1a,2p,3p,4a",

"reception_num":50,

"hospital_id":128,

"hospital _ name": six medicines of city,

"hospital_sort":"100",

"department_id":10,

"department _ name": cardiology department ",

"factor _ kill": cardiovascular disease ",

.

}

a user enters 39 hospital workstation APP by using a mobile phone or ipad, relevant information is input by keyword query, a request is sent to a WEB end PHP service for conversion, the PHP service sends the request to an ElasticSearch search engine for fast, accurate and word segmentation query of keywords, and information is returned to the PHP service and then to the user end APP. The data of the ElasticSearch search engine is derived from the MYSQL database, and all doctor-related data are exported to the ElasticSearch search engine every other preset time through a data synchronization service program. The method supports the keyword word segmentation function, obtains results according to near real-time query of the keywords and outputs the results in a sequence according to the relevancy of the keywords, achieves the effect that 39 doctor workstations quickly and accurately query the results according to the keywords and obtain information according to the relevancy of the keywords in a word segmentation mode, and reduces the writing of developers for querying SQL sentences in large space.

Corresponding to the embodiment of the method for searching the doctor information in the inquiry platform, the invention also provides an embodiment of a system for searching the doctor information in the inquiry platform. Fig. 5 is a schematic structural diagram of a system for searching doctor information in an inquiry platform according to an embodiment of the present disclosure, and fig. 6 is a schematic structural diagram of an ES server according to an embodiment of the present disclosure.

The system comprises a WEB server 001, a MYSQL database 002 and an ES server 003.

The ES server 003 includes:

an obtaining unit 301, configured to obtain a json string according to a keyword input by a user;

a search unit 302, configured to write a first DQL statement according to the json string;

a delivery unit 303, configured to output a preset number of search results from the keyword sorting results to a user.

Further, the obtaining unit 301 is further configured to:

and checking the validity of the json string.

Further, the search unit 302 is configured to:

inquiring all information with keyword prefixes;

inquiring all information with keyword phrases;

all the information contained in the keywords is queried.

Further, the system for searching doctor information in the interrogation platform further includes a data synchronization service unit 304, configured to:

and acquiring doctor information data from the MYSQL database according to a preset period. The data synchronization service unit 304 may be disposed in the ES server, or may be disposed independently, and is not limited herein.

Further, the data synchronization service unit 304 is configured to:

assembling an sql statement of the query;

assembling a second DQL statement which can be identified by the ES server;

According to the method for searching doctor information in the inquiry platform, the embodiment of the application also provides a readable storage medium and computer equipment. The readable storage medium stores executable program, and the program is executed by the processor to realize the steps of the method for searching doctor information in the inquiry platform; the computer device comprises a memory, a processor and an executable program stored on the memory and capable of running on the processor, wherein the processor realizes the steps of the method for searching the doctor information in the inquiry platform when executing the program.

The present application has been described in detail with reference to specific embodiments and illustrative examples, but the description is not intended to limit the application. Those skilled in the art will appreciate that various equivalent substitutions, modifications or improvements may be made to the presently disclosed embodiments and implementations thereof without departing from the spirit and scope of the present disclosure, and these fall within the scope of the present disclosure. The protection scope of this application is subject to the appended claims.

Claims

1. A method for physician information search in an interrogation platform, the method comprising:

acquiring a json string according to a keyword input by a user;

writing a first DQL statement according to the json string;

2. The method for physician information search in an interrogation platform of claim 1, wherein before writing the json string as a first DQL statement, further comprising:

and checking the validity of the json string.

3. The method for searching for doctor information in an interrogation platform according to claim 2, wherein performing word segmentation search according to the first DQL statement to obtain keyword search results comprises:

inquiring all information with keyword prefixes;

inquiring all information with keyword phrases;

all the information contained in the keywords is queried.

4. The method for physician information search in an interrogation platform of claim 1, further comprising:

5. The method for searching doctor information in an inquiry platform according to claim 4, wherein the step of obtaining doctor information data from the MYSQL database according to the preset period comprises the following steps:

assembling an sql statement of the query;

assembling a second DQL statement which can be identified by the ES server;

6. A system for searching doctor information in an inquiry platform comprises a WEB server, a MYSQL database and an ES server; the ES server includes:

7. The system for physician information search in an interrogation platform of claim 6, wherein the acquisition unit is further configured to:

and checking the validity of the json string.

8. The system for student information search in an interrogation platform of claim 7, wherein the search unit is configured to:

inquiring all information with keyword prefixes;

inquiring all information with keyword phrases;

all the information contained in the keywords is queried.

9. The system for physician information search in an interrogation platform of claim 6, further comprising a data synchronization service unit for:

10. The system for physician information search in an interrogation platform of claim 9, wherein the data synchronization service unit is configured to:

assembling an sql statement of the query;

assembling a second DQL statement which can be identified by the ES server;