CN116226511A

CN116226511A - Data query method, device, equipment and medium applied to data center station

Info

Publication number: CN116226511A
Application number: CN202211606444.0A
Authority: CN
Inventors: 贾小强; 李文竹
Original assignee: Beijing Yuannian Technology Co ltd
Current assignee: Beijing Yuannian Technology Co ltd
Priority date: 2022-12-14
Filing date: 2022-12-14
Publication date: 2023-06-06

Abstract

The application provides a data query method, a data query device, electronic equipment and a computer readable storage medium applied to a data center, wherein the method comprises the following steps: under the condition of acquiring query information input by a user, dividing the query information into at least two keywords; respectively inquiring historical occurrence times of corresponding keywords in a database based on the keywords; comparing the historical occurrence times of each keyword to generate a first comparison result; determining the priority of each keyword based on the first comparison result; the keywords are queried based on the priority of each keyword. The method and the device solve the technical problem that in the prior art, when query information input by a user comprises a plurality of keywords, the keywords can only be queried through the input sequence of the keywords, so that the query efficiency is low.

Description

Data query method, device, equipment and medium applied to data center station

Technical Field

The present invention relates to the field of data query, and in particular, to a data query method and apparatus for a data center, an electronic device, and a computer readable storage medium.

Background

With the rapid development of the internet, more and more services are provided for users, such as search services, communication services and the like, so that the requirements of the users are greatly met. Search engines are one of the basic services of the internet, and more users are used to searching for information through search engines.

In the prior art, information such as material information, product information, personnel information and the like of a company are all filed in a database of a middle platform, when data query is performed, a user inputs query information in a search box, a search engine queries keywords according to the keyword sequence in the query information input by the user, a query result is obtained, and the query result is returned to the user.

However, when the query information input by the user includes a plurality of keywords, the keywords can be queried only by the input order of the keywords, resulting in low query efficiency.

Based on this, the present invention has been made.

Disclosure of Invention

The purpose of the application is to provide a data query method, a device, electronic equipment and a computer readable storage medium applied to a data center, which solve the technical problem that in the prior art, when query information input by a user contains a plurality of keywords, the keywords can only be queried through the input sequence of the keywords, so that the query efficiency is low.

According to a first aspect of the present application, there is provided a data query method applied to a data center, the method comprising: under the condition of acquiring query information input by a user, dividing the query information into at least two keywords;

respectively inquiring historical occurrence times of corresponding keywords in a database based on the keywords;

comparing the historical occurrence times of each keyword to generate a first comparison result;

determining the priority of each keyword based on the first comparison result;

the keywords are queried based on the priority of each keyword.

Optionally, determining the priority of each keyword based on the first comparison result includes:

identifying priorities of the plurality of keywords based on the comparison result when the first comparison result is that the historical occurrence times of each keyword are different; or alternatively, the first and second heat exchangers may be,

when the historical occurrence times of at least two keywords are the same, acquiring the input sequence of the keywords with the same historical occurrence times;

identifying priorities of keywords with different historical occurrence times based on the first comparison result;

after the priorities of the keywords having different numbers of occurrence of the history are identified, the priorities of the keywords having the same number of occurrence of the history are identified based on the input order of the keywords.

Optionally, when the first comparison result is that the historical occurrence number of each keyword is different, identifying the priorities of the plurality of keywords based on the first comparison result includes:

when the first comparison result shows that the historical occurrence times of each keyword are different, determining the priority of the historical occurrence times of each keyword according to the sequence from less to more; wherein, the keyword with the least historical occurrence frequency has the highest priority, and the keyword with the most historical occurrence frequency has the lowest priority;

after identifying the priorities of the keywords having different historic occurrence numbers, identifying the priorities of the keywords having the same historic occurrence number based on the input order of the keywords, comprising:

after keywords with different historical occurrence times are determined according to the priorities from less to more, the keywords with the same historical occurrence times are identified according to the input sequence; wherein, the keyword priority of the input is higher than the keyword priority of the input.

Optionally, after querying the keywords based on the priority of each keyword, the method further includes:

generating a query result after querying the keywords based on the priority of each keyword;

When the query result is a plurality of query results, acquiring the total number of keywords in each query result;

when the total number of the keywords in each query result is different, sorting the query results based on the total number of the keywords in each query result; or alternatively, the first and second heat exchangers may be,

when the total number of keywords of at least two query results is the same, sorting the query results with different total numbers of keywords according to the total number of keywords;

comparing the first keywords in the query results with the same total number of keywords to generate a second comparison result;

when the second comparison result is that the number of the first keywords is the same, comparing the next keywords to generate a third comparison result, and the like until the fact that the number of the compared keywords is inconsistent is determined;

ranking the query results based on the number of individual keywords compared;

and displaying all the query results based on the ordering of each query result.

Optionally, the method further comprises: and under the condition that the number of each keyword in the plurality of query results is the same, the plurality of query results are arranged randomly.

Optionally, when the total number of keywords in each query result is different, sorting the query results based on the total number of keywords in each query result includes:

When the total number of the keywords of each query result is different, the query result with the largest total number of the keywords is at the forefront, and the query result with the smallest total number of the keywords is at the rearmost;

ranking the query results based on the number of individual keywords compared, including;

sorting the query results according to the sequence of the number of the compared keywords from more to less; wherein the query results with more than the number of the compared keywords are before the query results with less than the number of the compared keywords.

Optionally, querying the historical occurrence times of the corresponding keywords in the database based on the plurality of keywords respectively includes:

determining a keyword with the relativity exceeding a preset threshold value with each keyword as a recommended keyword based on the keywords;

inquiring historical occurrence times of corresponding keywords and corresponding recommended keywords in the database respectively based on the plurality of keywords and the recommended keywords;

comparing the historical occurrence times of each keyword to generate a first comparison result, wherein the first comparison result comprises the following steps:

and comparing the historical occurrence times of each keyword and the historical occurrence times of each recommended keyword to generate a first comparison result.

According to a second aspect of the present application, there is provided a data querying device for use in a data center, the device comprising: the dividing module is used for dividing the query information into at least two keywords under the condition of acquiring the query information input by the user; the first query module is used for respectively querying the historical occurrence times of the corresponding keywords in the database based on the plurality of keywords; the first comparison module is used for comparing the historical occurrence times of each keyword to generate a first comparison result; a determining module, configured to determine a priority of each keyword based on the first comparison result; and the second query module is used for querying the keywords based on the priority of each keyword.

Optionally, the determining module includes: the first recognition unit is used for recognizing the priority of the plurality of keywords based on the comparison result when the first comparison result is that the historical occurrence times of each keyword are different; or when the historical occurrence times of at least two keywords are the same, acquiring the input sequence of the keywords with the same historical occurrence times; the second recognition unit is used for recognizing the priorities of the keywords with different times of occurrence of the histories based on the first comparison result; the third recognition unit recognizes the priorities of the keywords having the same number of occurrence of history based on the input order of the keywords after recognizing the priorities of the keywords having different numbers of occurrence of history.

Optionally, the first identifying unit is configured to determine the priority according to the order from the low number to the high number when the first comparison result is that the historical occurrence number of each keyword is different; wherein, the keyword with the least historical occurrence frequency has the highest priority, and the keyword with the most historical occurrence frequency has the lowest priority; a third recognition unit, configured to recognize the keywords with the same number of occurrence times according to the input order after determining the priorities of the keywords with different number of occurrence times according to the number of occurrence times from less to more; wherein, the keyword priority of the input is higher than the keyword priority of the input.

Optionally, the apparatus further comprises: the generation module is used for generating a query result after the keywords are queried based on the priority of each keyword; the acquisition module is used for acquiring the total number of keywords in each query result when the query result is a plurality of query results; the first ordering module is used for ordering the query results based on the total number of the keywords in each query result when the total number of the keywords in each query result is different; or when the total number of the keywords of at least two query results is the same, sorting the query results with different total numbers of the keywords according to the total number of the keywords; the second comparison module is used for comparing the first keywords in the query results with the same total number of keywords to generate a second comparison result; the third comparison module is used for comparing the next keywords when the second comparison result is the same as the first keywords, so as to generate a third comparison result, and the like until the fact that the numbers of the compared keywords are inconsistent is determined; the second ordering module is used for ordering the query results based on the number of the compared single keywords; and the display module is used for displaying all the query results based on the ordering of each query result.

Optionally, the apparatus further comprises: and the third ordering module is used for randomly arranging the plurality of query results under the condition that the number of each keyword in the plurality of query results is the same.

Optionally, the first sorting module is configured to, when the total number of keywords of each query result is different, place the query result with the largest total number of keywords at the forefront and the query result with the smallest total number of keywords at the rearmost; the second ordering module is used for ordering the query results according to the order of the number of the compared keywords from more to less; wherein the query results with more than the number of the compared keywords are before the query results with less than the number of the compared keywords.

Optionally, the first query module is configured to determine, based on the plurality of keywords, a keyword, where a degree of correlation with each keyword exceeds a preset threshold, as a recommended keyword; inquiring historical occurrence times of corresponding keywords and corresponding recommended keywords in the database respectively based on the plurality of keywords and the recommended keywords; the first comparison module is used for comparing the historical occurrence times of each keyword and the historical occurrence times of each recommended keyword to generate a first comparison result.

According to a third aspect of the present application, there is provided an electronic device comprising a processor, a memory and a program or instructions stored on the memory and executable on the processor, the program or instructions when executed by the processor implementing the steps of the data querying method as shown in the first aspect as applied to a data center.

According to a fourth aspect of the present application, there is provided a readable storage medium having stored thereon a program or instructions which, when executed by a processor, implement the steps of the data querying method as shown in the first aspect applied to a data center.

The CPU can establish a communication relation with the data center, wherein the CPU divides query information into at least two keywords under the condition that query information input by a user to the data center is acquired, the number of times of occurrence of keyword histories in a database is queried according to each keyword, a first comparison result is generated by comparing the number of times of occurrence of each keyword histories, then the priority of each keyword searching sequence is determined according to the first comparison result, then the keywords are queried according to the priority, namely, the query result of the query information is determined according to the priority of each keyword in the query information, and data wanted by the user can be queried efficiently under the condition that the number of keyword data in the query information is more. The method and the device solve the technical problem that in the prior art, when query information input by a user comprises a plurality of keywords, the keywords can only be queried through the input sequence of the keywords, so that the query efficiency is low.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a flowchart of a data query method applied to a data center station according to an embodiment of the present application;

fig. 2 is a flowchart of a data query method applied to a data center station according to an embodiment of the present application;

fig. 3 is a flowchart of a data query method applied to a data center station according to an embodiment of the present application; and

fig. 4 is a schematic diagram of a data query device applied to a data center station according to an embodiment of the present application.

Detailed Description

To further clarify the above and other features and advantages of the present application, a further description of the present application is provided below with reference to the appended drawings. It should be understood that the specific embodiments presented herein are for purposes of explanation to those skilled in the art and are intended to be illustrative only and not limiting.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. However, it will be apparent to one of ordinary skill in the art that the specific details need not be employed to practice the present application. In other instances, well-known steps or services have not been described in detail in order to avoid obscuring the present application.

Based on the content of the background art, in the prior art, when the query information input by the user includes a plurality of keywords, the keywords can only be queried according to the input sequence of the keywords, which results in low query efficiency.

In order to solve the technical problems, the application provides a data query method, a data query device, electronic equipment and a computer readable storage medium applied to a data center. The data query method applied to the data center station provided by the application is described in detail through specific embodiments and application scenes thereof with reference to the accompanying drawings.

As shown in fig. 1, the present application provides a data query method applied to a data center, where the method may include:

step S11: under the condition that query information input by a user is acquired, the query information is divided into at least two keywords.

Specifically, in the present application, a central processing unit (Central Processing Unit, CPU) may be used as an execution body of the present application, the CPU may establish a communication relationship with a data center, first, a search box is set in the data center, and then, a user may input data information to be queried in the search box; after the user inputs the query information, the CPU may divide the query information into at least two keywords. Such as: the query information is a product B of 09 years of company A, and then the query information is divided into three keywords of company A, company 09 years and product B, so that the judgment of the priority of each keyword in the subsequent steps is facilitated.

Step S13: and respectively inquiring the historical occurrence times of the corresponding keywords in the database based on the plurality of keywords.

Specifically, in this application, after dividing the query information into a plurality of keywords, according to the data information of the plurality of keywords, the historical occurrence number of each keyword in the database is queried, and still taking the query information as an example of a product of a company for 09 years B, the query information is divided into three keywords of "company a", "09 years" and "product B", and then the historical occurrence numbers of "company a", "09 years" and "product B" need to be queried in the database respectively, for example: company a appeared 10 times, 5 times in 09 years, and product B appeared 100 times.

In order to make the query results of the query information in the query database more accurate, in an alternative embodiment, step S13 includes:

and determining keywords with the relevance exceeding a preset threshold value with each keyword based on the plurality of keywords as recommended keywords.

And respectively inquiring historical occurrence times of the corresponding keywords and the corresponding recommended keywords in the database based on the plurality of keywords and the recommended keywords.

Specifically, in the present application, if the keyword to be queried exists in the database, but the keyword input by the user has a small difference from the keyword name stored in the database, the query load is heavy, the efficiency is low, and even the query cannot be performed. Such as: the query information input by the user is the product of company A, 09 years B. However, company a is also often called a department for short, so the user inputs "a department 09 years B product", at this time, after keywords are grouped, only 09 years and B products can be matched with keywords pre-stored in the data center system, but a department cannot be matched, so that only 2 groups (09 years and B products) of valid keywords are required when querying. Therefore, after the query information is divided into a plurality of keywords, the recommended keywords related to the keywords are queried according to the plurality of keywords, namely, the keywords with the degree of relevance exceeding a preset threshold value are used as the recommended keywords. The preset threshold may be 5 times. It should be noted that the relevance may be the number of times of the preset keyword that is finally determined to be downloaded after the keyword is queried. Taking the query information as the product of company a in 09 years, if company a is searched for each time, it is finally identified that the selected, downloaded and opened product is company a, and the number of times exceeds 5, then company a is regarded as the recommended keyword of company a. After the recommended keywords of the keywords are identified, historical occurrence times in the database corresponding to the keywords and the recommended keywords can be queried, so that the accuracy of query results of query information in the query database can be effectively improved, the query efficiency can be increased, and network resources occupied in the query process can be reduced.

In an alternative embodiment, if each search for A-company, B-company, and C-company are ultimately identified as being selected, downloaded, and opened, and more than 5 times, A-company, B-company, and C-company are associated.

In an alternative embodiment, if a company is searched for each time, it is finally identified that all of the company a, the company B and the company C are selected, downloaded and opened, wherein the number of times the company a is selected, downloaded and opened is much greater than that of the company B and the company C. It should be noted that, here, the number of times is far greater than 5, and only a is finally associated with a company. In this application, the number of times that is far greater may be more than 5 times, such as: 10 times, 15 times, etc., the higher the number of times, the greater the degree of association between the two, and thus the higher the association authenticity.

In an alternative embodiment, if A department is not queried each time A department is entered, but the data center is matched to be the closest to A department, then popup and text query "please ask if A department is to be found", if the user selects yes, the CPU controls the center data system to automatically save A department and A company.

In an alternative embodiment, the historical occurrence number of the keywords may be stored in the middle data system for each item, the system identifies the names of the stored items, then groups the keywords with the names of the items, and then counts the historical occurrence number of the keywords. That is, the number of times of occurrence of the history of each keyword is stored in advance.

For example: 4 items are stored in the system, and the names of the items are as follows: company a 09 years B product, company a 11 years B product, company C09 years F product.

After keyword grouping: the frequency of occurrence of the company A is 2, the frequency of occurrence of 09 years is 2, the frequency of occurrence of 11 years is 2, the frequency of occurrence of the product B is 3, and the frequency of occurrence of the product F is 1.

The number of times of pre-storing the keywords in the database can save the inquiry time. The prestored basis is statistics of keywords which are commonly inquired by inquirers.

Based on the above, that is, the total amount of keywords pre-stored in the system is varied.

Specifically, for example, if a query person queries company a, the subsequent system will store company a as a pre-stored keyword and make statistics; therefore, when the inquiring person inquires the company A again next time, the system can rapidly count the times of the company A in each search result because the system has prestored the keyword and counts the keyword, so that the time for temporarily acquiring the keyword by the system to count the keyword can be saved. It can be further understood by those skilled in the art that the keywords pre-stored in the system can be updated according to the query frequency of the query personnel, and the keywords with lower query frequency can be deleted, so that the pre-stored space of the system is saved. The keyword update time in a specific system can be set by a person skilled in the art according to the need.

Step S15: and comparing the historical occurrence times of each keyword to generate a first comparison result.

Specifically, in the present application, after the number of occurrence times of each keyword history is obtained, the number of occurrence times of each keyword history is compared, so as to generate a first comparison result. Still take query information as a product of company a for 09 years B as an example. Wherein, company a appears 10 times, and appears 5 times in 09 years, and product B appears 100 times, then the comparison result generated may be: the historical appearance times of the B product are larger than that of the A company and are larger than that of 09 years.

In order to improve the query effect, in an alternative embodiment, step S15 includes: and comparing the historical occurrence times of each keyword and the historical occurrence times of each recommended keyword to generate a first comparison result.

Specifically, in the present application, after a keyword and a recommended keyword associated with the keyword are queried, the historical occurrence times of each keyword are sequentially compared, and a first comparison result is generated. According to the method and the device for comparing the keywords, the comparison of the recommended keywords is considered while the comparison of the keywords is carried out, so that the query efficiency is effectively improved.

Step S17: the priority of each keyword is determined based on the first comparison result.

Specifically, in the present application, after the first comparison result is obtained, the priority of each keyword is determined according to the first comparison result. Still take query information as a product of company a for 09 years B as an example. Wherein, company a appears 10 times, and appears 5 times in 09 years, and product B appears 100 times, then the first comparison result generated may be: the historical appearance times of the B products are larger than the historical appearance times of the A company and larger than the historical appearance times of 09 years, or the historical appearance times of the A company are smaller than the historical appearance times of the B products, and then the priority of each keyword can be determined according to the first comparison result. Compared with the prior art that the priority is determined by using the keyword input sequencing way, the method and the device for determining the priority according to the historical occurrence times of the determined keywords can effectively improve query efficiency.

As shown in fig. 2, in order to make keyword priority determination more accurate, in an alternative embodiment, step S17 includes:

step S171: identifying priorities of the plurality of keywords based on the comparison result when the first comparison result is that the historical occurrence times of each keyword are different; or when the historical occurrence times of at least two keywords are the same, acquiring the input sequence of the keywords with the same historical occurrence times.

Step S172: and identifying the priorities of the keywords with different historical occurrence times based on the first comparison result.

Step S173: after the priorities of the keywords having different numbers of occurrence of the history are identified, the priorities of the keywords having the same number of occurrence of the history are identified based on the input order of the keywords.

Specifically, in the present application, two ways of determining keyword priorities are provided. The method comprises the following steps: when the historical occurrence times of each keyword are different, the priorities of a plurality of keywords can be identified directly according to the comparison result; and two,: when the historic occurrence times of at least two keywords are the same, priorities of the keywords having different historic occurrence times can be identified first. Such as: the information is a product B of 09 years and 05 months of company A, wherein the historical occurrence number of company A is 100 times, the historical occurrence number of 09 years is 100 times, the historical occurrence number of month 05 is 50 times, and the historical occurrence number of product B is 30 times, and the comparison result can be: the historical appearance times of the A company are larger than the historical appearance times of the B product when the historical appearance times of 09 years are larger than the historical appearance times of 05 months. That is, the historical occurrence number of the a company and the historical occurrence number of the 09 years cannot be judged at present, the application can obtain the input sequence of the two keywords of the a company and the 09 years, and then judge the priority of the a company and the 09 years according to the input sequence, so that the priority judgment of the keywords can be more accurate.

In an alternative embodiment, the priorities of the keywords with the same number of occurrence times of the history may be identified first, and then the priorities of the keywords with different numbers of occurrence times of the history may be identified.

In an alternative embodiment, when the number of times of occurrence of the history of each keyword is different as the first comparison result in step S171, identifying the priorities of the plurality of keywords based on the comparison result includes: when the first comparison result shows that the historical occurrence times of each keyword are different, determining the priority of the historical occurrence times of each keyword according to the sequence from less to more; wherein, the keyword with the least historical occurrence frequency has the highest priority, and the keyword with the most historical occurrence frequency has the lowest priority.

Specifically, in the present application, when the first comparison result is that the history occurrence number of each keyword is different, the priority may be determined according to the order from the least to the more of the history occurrence numbers of the keywords, and it should be noted that the keyword with the least history occurrence number has the highest priority, and the keyword with the most history occurrence number has the lowest priority, that is, the keyword with the least history occurrence number is preferentially searched, then the keyword with the most occurrence number is searched, and finally the keyword with the most search occurrence number is searched. Still take information as a product B of a company 09 years as an example, wherein the number of times of occurrence of the history of the company a is 100 times, the number of times of occurrence of the history of the company 09 years is 50 times, and the number of times of occurrence of the history of the product B is 30 times, and then the priority of the company a is lower than the priority of the product B in 09 years. Because the fewer the historical query times in the database, the fewer the selected items, the query efficiency can be effectively increased in a manner of determining the priority of the application.

Step S173 includes: after keywords with different historical occurrence times are determined according to the priorities from less to more, the keywords with the same historical occurrence times are identified according to the input sequence; wherein, the keyword priority of the input is higher than the keyword priority of the input.

Specifically, in the present application, after determining priorities from less to more for keywords with different times of occurrence of history, the keywords with the same times of occurrence of history need to be identified in order, and it should be noted that the priorities of the keywords input first are higher than the priorities of the keywords input later. Taking the query information as a product B of 09 years 05 month of company a as an example, wherein the number of times of occurrence of the history of company a is 100 times, the number of times of occurrence of the history of year 09 is 100 times, the number of times of occurrence of history of month 05 is 50 times, and the number of times of occurrence of history of product B is 30 times, after the priorities of the keywords with different numbers of times of occurrence of history are ordered, that is, after the priority of the product B with a priority of more than month 05 is greater than that of company a and 09 years, if the company a inputs before the year 09, the priorities of the keywords are as follows: the priority of the B product is higher than that of the A company for more than 09 years in the month of more than 05; if company a inputs later than 09 years, the priorities of the keywords are: the priority of the B product is higher than that of the A company in the period of more than 05 months and more than that of the B product in the period of more than 09 years. Because the importance of each keyword to the user query information can be known according to the input sequence of the user, the importance of the keyword input first is higher than that of the keyword input later, so that the user desired item can be queried more quickly and accurately.

Step S19: the keywords are queried based on the priority of each keyword.

Specifically, in the present application, after determining the priority of each keyword, each keyword is queried according to the priority.

Compared with the prior art, the method and the device for inquiring the data of the user can determine the inquiring result of the inquiring information according to the priority of each keyword in the inquiring information, and can inquire the data wanted by the user with high efficiency under the condition that the keyword data in the inquiring information is more. The method and the device solve the technical problem that in the prior art, when query information input by a user comprises a plurality of keywords, the keywords can only be queried through the input sequence of the keywords, so that the query efficiency is low.

In addition, when the keywords are queried, the related keywords related to the keywords are queried, so that the query efficiency and the query accuracy can be increased more effectively.

In an alternative embodiment, as shown in fig. 3, after step S19, the method further comprises:

step S21: after the keywords are queried based on the priority of each keyword, a query result is generated.

Step S23: and when the query result is a plurality of query results, acquiring the total number of keywords in each query result.

Step S25: when the total number of the keywords in each query result is different, sorting the query results based on the total number of the keywords in each query result; or when the total number of the keywords of at least two query results is the same, sorting the query results with different total numbers of the keywords according to the total number of the keywords.

Specifically, in the present application, after each keyword is queried according to the priority of the keyword, a query result is generated. Wherein, the number of the query results can be one or more, and when the query result is one query result, the query result is directly displayed; when the number of the query results is multiple, the total number of keywords of each query result in the multiple query results is required to be obtained, and under the condition that the total number of keywords of each query result is different, the multiple query results are ordered based on the total number of the keywords, so that the query efficiency can be effectively improved.

And under the condition that the total number of the keywords of at least two query results is the same, firstly sorting the query results with different total numbers of the keywords according to the total numbers of the keywords. Such as: in one query result, 10 times appear in company A, 10 times appear in 09 years, 20 times appear in product B, the total number of times of keyword appearance is 40 times, another query result is 10 times appear in company A, 20 times appear in 09 years, 10 times appear in product B, the total number of times of keyword appearance is 40 times, another query result is 10 times appear in company A, 10 times appear in 09 years, 10 times appear in product B, the total number of times of keyword appearance is 30 times, then the query results with the total number of keywords of 30 times and the total number of keywords of 40 times are firstly sequenced, and the same total number of keywords are sequenced after the different waiting keyword total numbers are sequenced.

In an alternative embodiment, the query results with the same total number of keywords may be ranked first, and then the query results with different total numbers of keywords may be ranked.

Step S27: and comparing the first keywords in the query results with the same total number of keywords to generate a second comparison result.

Step S29: and when the second comparison result is that the number of the first keywords is the same, comparing the next keywords to generate a third comparison result, and the like until the fact that the number of the compared keywords is inconsistent is determined.

Step S31: the query results are ranked based on the number of individual keywords that are compared.

Step S33: and displaying all the query results based on the ordering of each query result.

Specifically, in the present application, in the query results with the same total number of keywords, the number of the keywords belonging to the first keyword is compared, so as to generate a second comparison result. It should be noted that, the keywords in the query result may be arranged in a left-to-right order, such as a first keyword, a second keyword, etc.; the keywords may be arranged in the order entered by the user or in the order set by the user. Under the condition that the number of the first keywords is different, sorting query results with the same total number of the keywords according to the number of the first keywords; and under the condition that the total number of the first keywords is the same, comparing the number of the second keywords to generate a third comparison result, and the like until the fact that the number of the compared keywords is inconsistent is determined. Such as: the method comprises the steps that company A appears 10 times, 10 times in 09 years, 20 times in B products appear, the total number of keyword appearance times is 40 times, one query result is that company A appears 10 times, 20 times in 09 years, 10 times in B products appear, the total number of keyword appearance times is 40 times, the total number of two query results is the same, the first keyword number is the same, the second keyword number is different, and then the second keyword number is taken as a judgment basis, namely, the ordering of the two query results is determined according to the total number of the second keywords.

To order the query results more accurately, in an alternative embodiment, when the total number of keywords in each query result is different in step S25, the ranking the query results based on the total number of keywords in each query result includes: when the total number of keywords of each query result is different, the query result with the largest total number of keywords is at the forefront, and the query result with the smallest total number of keywords is at the rearmost.

Specifically, in the present application, when the total number of keywords of each query result is different, each query result is ranked according to the total number of keywords, where the query result with the largest total number of keywords is at the forefront and the query result with the smallest number of keywords is at the rearmost. Such as: in a certain query result, company A appears 10 times, 10 times in 09 years, and product B appears 20 times, and the total number of times of keyword appearance is 40 times. Another query result keyword appears a total number of times of 30, then the total number of query result keywords is 40 and is between 30 times. Because the more frequently the keywords appear, the stronger the relevance with the information to be searched is, the query results can be more accurately sequenced according to the sequencing mode in the application, so that the user can more quickly and intuitively see the query results.

It should be noted that the query results are arranged in the order from top to bottom, that is, the query result with the largest total number of keywords is at the front (top), and the query result with the smallest number of keywords is at the rear (bottom).

Step S31 includes: sorting the query results according to the sequence of the number of the compared keywords from more to less; wherein the query results with more than the number of the compared keywords are before the query results with less than the number of the compared keywords.

Specifically, in the application, in the query results with the same total number, the more the number of times that the front keyword appears, the stronger the correlation with the information to be searched is considered, so that the query results can be more accurately ranked, and the user can more quickly and intuitively see the query results.

In an alternative embodiment, the method further comprises: and under the condition that the number of each keyword in the plurality of query results is the same, the plurality of query results are arranged randomly.

Specifically, in the present application, in the query results with the same total number of the plurality of keywords, the total number of the single keywords is also the same, and then the query results with the same total number of the plurality of keywords are arranged randomly. Such as: the method comprises the steps that company A appears 10 times, 10 times in 09 years, 20 times in product B, the total number of keyword appearance times is 40 times, the other query result is that company A appears 10 times, 10 times in 09 years, 20 times in product B, the total number of keyword appearance times is 40 times, wherein the total number of keywords of the query result is the same, the number of single keywords is the same, and then the two comparison results are arranged randomly.

It should be noted that, the method is limited to the query results that the total number of the plurality of keywords is the same and the number of the single keywords is also the same.

In addition, when the query results are displayed, the query results can be ranked according to the number of keywords of each query result, so that the query results can be ranked more accurately, and a user can see the query results more quickly and intuitively.

As shown in fig. 4, in an alternative embodiment, there is provided a data query apparatus applied to a data center station, the apparatus comprising: a dividing module 41, configured to divide query information into at least two keywords in a case of acquiring the query information input by a user; a first query module 42, configured to query the database for historical occurrence times of corresponding keywords based on the plurality of keywords, respectively; a first comparison module 43, configured to compare the historical occurrence times of each keyword to generate a first comparison result; a determining module 44, configured to determine a priority of each keyword based on the first comparison result; a second query module 45, configured to query the keywords based on the priority of each keyword.

Specifically, a central processing unit (Central Processing Unit, CPU) may be used as an execution subject of the present application, the CPU may establish a communication relationship with a data center, first, a search box is set in the data center, and then a user may input data information to be queried in the search box; after the user inputs the query information, the CPU may divide the query information into at least two keywords. Such as: the query information is a product B of 09 years of company A, and then the query information is divided into three keywords of company A, company 09 years and product B, so that the judgment of the priority of each keyword in the subsequent steps is facilitated. After dividing the query information into a plurality of keywords, according to the data information of the keywords, querying the historical occurrence number of each keyword in the database, taking the query information as an example of a product of 09 years B of an a company, and dividing the query information into three keywords of "a company", "09 years" and "B product", then respectively querying the database for the historical occurrence number of "a company", "09 years" and "B product", for example: company a appeared 10 times, 5 times in 09 years, and product B appeared 100 times. After the historical occurrence times of each keyword are obtained, the historical occurrence times of each keyword are compared, and a first comparison result is generated. Still take query information as a product of company a for 09 years B as an example. Wherein, company a appears 10 times, and appears 5 times in 09 years, and product B appears 100 times, then the comparison result generated may be: the historical appearance times of the B product are larger than that of the A company and are larger than that of 09 years. After the first comparison result is obtained, the priority of each keyword is determined according to the first comparison result. Still take query information as a product of company a for 09 years B as an example. Wherein, company a appears 10 times, and appears 5 times in 09 years, and product B appears 100 times, then the first comparison result generated may be: the historical appearance times of the B products are larger than the historical appearance times of the A company and larger than the historical appearance times of 09 years, or the historical appearance times of the A company are smaller than the historical appearance times of the B products, and then the priority of each keyword can be determined according to the first comparison result. Compared with the prior art that the priority is determined by using the keyword input sequencing way, the method and the device for determining the priority according to the historical occurrence times of the determined keywords can effectively improve query efficiency. Wherein, after determining the priority of each keyword, each keyword is queried according to the priority.

Optionally, the determining module 44 includes: the first recognition unit is used for recognizing the priority of the plurality of keywords based on the comparison result when the first comparison result is that the historical occurrence times of each keyword are different; or when the historical occurrence times of at least two keywords are the same, acquiring the input sequence of the keywords with the same historical occurrence times; the second recognition unit is used for recognizing the priorities of the keywords with different times of occurrence of the histories based on the first comparison result; the third recognition unit recognizes the priorities of the keywords having the same number of occurrence of history based on the input order of the keywords after recognizing the priorities of the keywords having different numbers of occurrence of history.

Specifically, two ways of judging keyword priority are provided. The method comprises the following steps: when the historical occurrence times of each keyword are different, the priorities of a plurality of keywords can be identified directly according to the comparison result; and two,: when the historic occurrence times of at least two keywords are the same, priorities of the keywords having different historic occurrence times can be identified first. Such as: the information is a product B of 09 years and 05 months of company A, wherein the historical occurrence number of company A is 100 times, the historical occurrence number of 09 years is 100 times, the historical occurrence number of month 05 is 50 times, and the historical occurrence number of product B is 30 times, and the comparison result can be: the historical appearance times of the A company are larger than the historical appearance times of the B product when the historical appearance times of 09 years are larger than the historical appearance times of 05 months. That is, the historical occurrence number of the a company and the historical occurrence number of the 09 years cannot be judged at present, the application can obtain the input sequence of the two keywords of the a company and the 09 years, and then judge the priority of the a company and the 09 years according to the input sequence, so that the priority judgment of the keywords can be more accurate.

Specifically, when the first comparison result is that the historical occurrence times of each keyword are different, priorities can be determined according to the historical occurrence times of the keywords in order from less to more, and it is required to be explained that the keyword with the lowest historical occurrence times has the highest priority, that is, the keyword with the highest historical occurrence times has the lowest priority, that is, the keyword with the lowest occurrence times is preferentially searched, then the keyword with the occurrence times is searched, and finally the keyword with the highest search occurrence times is searched. Still take information as a product B of a company 09 years as an example, wherein the number of times of occurrence of the history of the company a is 100 times, the number of times of occurrence of the history of the company 09 years is 50 times, and the number of times of occurrence of the history of the product B is 30 times, and then the priority of the company a is lower than the priority of the product B in 09 years. Because the fewer the historical query times in the database, the fewer the selected items, the query efficiency can be effectively increased in a manner of determining the priority of the application. The keywords with different historical occurrence times are identified according to the sequence after the priorities are determined from less to more, and the priority of the keywords which are input first is higher than the priority of the keywords which are input later. Taking the query information as a product B of 09 years 05 month of company a as an example, wherein the number of times of occurrence of the history of company a is 100 times, the number of times of occurrence of the history of year 09 is 100 times, the number of times of occurrence of history of month 05 is 50 times, and the number of times of occurrence of history of product B is 30 times, after the priorities of the keywords with different numbers of times of occurrence of history are ordered, that is, after the priority of the product B with a priority of more than month 05 is greater than that of company a and 09 years, if the company a inputs before the year 09, the priorities of the keywords are as follows: the priority of the B product is higher than that of the A company for more than 09 years in the month of more than 05; if company a inputs later than 09 years, the priorities of the keywords are: the priority of the B product is higher than that of the A company in the period of more than 05 months and more than that of the B product in the period of more than 09 years. Because the importance of each keyword to the user query information can be known according to the input sequence of the user, the importance of the keyword input first is higher than that of the keyword input later, so that the user desired item can be queried more quickly and accurately.

Specifically, after each keyword is queried according to the priority of the keyword, a query result is generated. Wherein, the number of the query results can be one or more, and when the query result is one query result, the query result is directly displayed; when the number of the query results is multiple, the total number of keywords of each query result in the multiple query results is required to be obtained, and under the condition that the total number of keywords of each query result is different, the multiple query results are ordered based on the total number of the keywords, so that the query efficiency can be effectively improved.

And comparing the quantity of the keywords belonging to the first keyword in the query results with the same total quantity of the keywords to generate a second comparison result. It should be noted that, the keywords in the query result may be arranged in a left-to-right order, such as a first keyword, a second keyword, etc.; the keywords may be arranged in the order entered by the user or in the order set by the user. Under the condition that the number of the first keywords is different, sorting query results with the same total number of the keywords according to the number of the first keywords; and under the condition that the total number of the first keywords is the same, comparing the number of the second keywords to generate a third comparison result, and the like until the fact that the number of the compared keywords is inconsistent is determined. Such as: the method comprises the steps that company A appears 10 times, 10 times in 09 years, 20 times in B products appear, the total number of keyword appearance times is 40 times, one query result is that company A appears 10 times, 20 times in 09 years, 10 times in B products appear, the total number of keyword appearance times is 40 times, the total number of two query results is the same, the first keyword number is the same, the second keyword number is different, and then the second keyword number is taken as a judgment basis, namely, the ordering of the two query results is determined according to the total number of the second keywords.

Specifically, in the query results with the same total number of the plurality of keywords, the total number of the single keywords is also the same, and then the query results with the same total number of the plurality of keywords are arranged randomly. Such as: the method comprises the steps that company A appears 10 times, 10 times in 09 years, 20 times in product B, the total number of keyword appearance times is 40 times, the other query result is that company A appears 10 times, 10 times in 09 years, 20 times in product B, the total number of keyword appearance times is 40 times, wherein the total number of keywords of the query result is the same, the number of single keywords is the same, and then the two comparison results are arranged randomly.

Specifically, when the total number of keywords of each query result is different, each query result is ranked according to the total number of keywords, wherein the query result with the largest total number of keywords is at the forefront, and the query result with the smallest keywords is at the rearmost. Such as: in a certain query result, company A appears 10 times, 10 times in 09 years, and product B appears 20 times, and the total number of times of keyword appearance is 40 times. Another query result keyword appears a total number of times of 30, then the total number of query result keywords is 40 and is between 30 times. Because the more frequently the keywords appear, the stronger the relevance with the information to be searched is, the query results can be more accurately sequenced according to the sequencing mode in the application, so that the user can more quickly and intuitively see the query results.

In addition, in the query results with the same total number, the more the number of times that the front keyword appears, the stronger the relevance with the information to be searched is considered, so that the query results can be more accurately ordered, and the user can more quickly and intuitively see the query results.

Optionally, the first query module 42 is configured to determine, based on the plurality of keywords, a keyword that has a relevance with respect to each keyword that exceeds a preset threshold as the recommended keyword; inquiring historical occurrence times of corresponding keywords and corresponding recommended keywords in the database respectively based on the plurality of keywords and the recommended keywords; the first comparison module is used for comparing the historical occurrence times of each keyword and the historical occurrence times of each recommended keyword to generate a first comparison result.

Specifically, if the keywords to be queried exist in the database, but the keywords input by the user have smaller differences from the keyword names stored in the database, the query load is heavier, the efficiency is lower, and even the query cannot be achieved. Such as: the query information input by the user is the product of company A, 09 years B. However, company a is also often called a department for short, so the user inputs "a department 09 years B product", at this time, after keywords are grouped, only 09 years and B products can be matched with keywords pre-stored in the data center system, but a department cannot be matched, so that only 2 groups (09 years and B products) of valid keywords are required when querying. Therefore, after the query information is divided into a plurality of keywords, the recommended keywords related to the keywords are queried according to the plurality of keywords, namely, the keywords with the degree of relevance exceeding a preset threshold value are used as the recommended keywords. The preset threshold may be 5 times. It should be noted that the relevance may be the number of times of the preset keyword that is finally determined to be downloaded after the keyword is queried. Taking the query information as the product of company a in 09 years, if company a is searched for each time, it is finally identified that the selected, downloaded and opened product is company a, and the number of times exceeds 5, then company a is regarded as the recommended keyword of company a. After the recommended keywords of the keywords are identified, historical occurrence times in the database corresponding to the keywords and the recommended keywords can be queried, so that the accuracy of query results of query information in the query database can be effectively improved, the query efficiency can be increased, and network resources occupied in the query process can be reduced. After the keywords and the recommended keywords associated with the keywords are queried, the historical occurrence times of each keyword are sequentially compared, and a first comparison result is generated. According to the method and the device for comparing the keywords, the comparison of the recommended keywords is considered while the comparison of the keywords is carried out, so that the query efficiency is effectively improved.

It is to be understood that the various modules/units of the apparatus of the present application may be implemented in whole or in part by software, hardware, firmware, or a combination thereof. Each module/unit may be embedded in the processor of the computer device in hardware or firmware form or independent of the processor, or may be stored in the memory of the computer device in software form for the processor to call to perform the services of each module/unit. Each module/unit may be implemented as a separate component or module, or two or more modules/units may be implemented as a single component or module.

In one embodiment, a computer device is provided that includes a memory and a processor, the memory having stored thereon computer instructions executable by the processor, the computer instructions, when executed by the processor, directing the processor to perform the steps of the methods of the present application. The computer device may be broadly a server, a terminal, or any other electronic device having the necessary computing and/or processing capabilities. In one embodiment, the computer device may include a processor, memory, network interface, communication interface, etc. connected by a system bus. The processor of the computer device may be used to provide the necessary computing, processing and/or control capabilities. The memory of the computer device may include a non-volatile storage medium and an internal memory. The non-volatile storage medium may have stored therein or thereon a service system, a computer program, or the like. The internal memory may provide an environment for the operation of the service system and computer programs in the non-volatile storage medium. The network interface and communication interface of the computer device may be used to connect and communicate with external devices via a network.

The present application may be implemented as a computer readable storage medium having stored thereon a computer program which, when executed by a processor, causes steps of a method of the present application to be performed. In one embodiment, a computer program is distributed over a plurality of computer devices or processors coupled by a network such that the computer program is stored, accessed, and executed by one or more computer devices or processors in a distributed fashion. A single method step/service, or two or more method steps/services, may be performed by a single computer device or processor, or by two or more computer devices or processors. One or more method steps/services may be performed by one or more computer devices or processors, and one or more other method steps/services may be performed by one or more other computer devices or processors. One or more computer devices or processors may perform a single method step/service, or perform two or more method steps/services.

Those of ordinary skill in the art will appreciate that the steps of the methods of the present application may be implemented by a computer program that instructs related hardware, such as a computer device or processor, to perform the steps of the methods of the present application, and that the computer program may be stored in a non-transitory computer readable storage medium, which when executed causes the steps of the methods of the present application to be performed. Any reference herein to memory, storage, database, or other medium may include non-volatile and/or volatile memory, as the case may be. Examples of nonvolatile memory include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), flash memory, magnetic tape, floppy disk, magneto-optical data storage, hard disk, solid state disk, and the like. Examples of volatile memory include Random Access Memory (RAM), external cache memory, and the like.

The technical features described above may be arbitrarily combined. Although not all possible combinations of features are described, any combination of features should be considered to be covered by the description provided that such combinations are not inconsistent.

While the present application has been described in conjunction with the embodiments, it is to be understood by those skilled in the art that the foregoing description and drawings are illustrative only and not limiting, and that the present application is not limited to the disclosed embodiments. Various modifications and variations are possible without departing from the spirit of the application.

Claims

1. A data query method applied to a data center, the method comprising:

under the condition of acquiring query information input by a user, dividing the query information into at least two keywords;

respectively inquiring historical occurrence times of the corresponding keywords in a database based on a plurality of the keywords;

determining the priority of each keyword based on the first comparison result;

and inquiring the keywords based on the priority of each keyword.

2. The data query method applied to a data center as claimed in claim 1, wherein determining the priority of each keyword based on the first comparison result comprises:

identifying priorities of a plurality of keywords based on the comparison result when the first comparison result is that the historical occurrence times of each keyword are different; or alternatively, the first and second heat exchangers may be,

After the priorities of the keywords having different history occurrence numbers are identified, the priorities of the keywords having the same history occurrence number are identified based on the input order of the keywords.

3. The data query method applied to a data center according to claim 2, wherein when the first comparison result is that the number of times of occurrence of history of each keyword is different, identifying priorities of a plurality of the keywords based on the first comparison result includes:

after identifying the priorities of the keywords with different historical occurrence times, identifying the priorities of the keywords with the same historical occurrence times based on the input sequence of the keywords, wherein the method comprises the following steps:

4. The data query method applied to a data center as claimed in claim 1, wherein after said querying said keywords based on the priority of each of said keywords, said method further comprises:

after inquiring the keywords based on the priority of each keyword, generating an inquiry result;

when the query result is a plurality of query results, acquiring the total number of the keywords in each query result;

when the total number of keywords of at least two query results is the same, sorting the query results with different total numbers of the keywords according to the total number of the keywords;

Ranking the query results based on the number of individual keywords compared;

5. The data query method applied to a data center as claimed in claim 4, wherein said method further comprises:

and under the condition that the number of each keyword in the plurality of query results is the same, the plurality of query results are arranged randomly.

6. The data query method applied to a data center as claimed in claim 4, wherein when the total number of keywords in each query result is different, ranking the query results based on the total number of keywords in each query result comprises:

when the total number of keywords of each query result is different, the query result with the largest total number of keywords is at the forefront, and the query result with the smallest total number of keywords is at the rearmost;

the method comprises the steps that query results are ordered based on the number of the compared single keywords, wherein the method comprises the steps of;

sorting the query results according to the order of the number of the compared keywords from more to less; wherein the query results with more than the number of the compared keywords are before the query results with less than the number of the compared keywords.

7. The data query method applied to a data center according to claim 1, wherein the querying the database based on the historical occurrence times of the keywords, respectively, includes:

determining keywords, the relevance of which to each keyword exceeds a preset threshold, as recommended keywords based on the keywords;

inquiring historical occurrence times corresponding to the keywords and the recommended keywords in a database respectively based on a plurality of the keywords and the recommended keywords;

comparing the historical occurrence times of each keyword to generate a first comparison result, wherein the first comparison result comprises the following steps of:

8. A data query device for use in a data center, the device comprising:

the dividing module is used for dividing the query information into at least two keywords under the condition of acquiring the query information input by a user;

the first query module is used for respectively querying historical occurrence times of the corresponding keywords in the database based on the keywords;

The first comparison module is used for comparing the historical occurrence times of each keyword to generate a first comparison result;

a determining module, configured to determine a priority of each keyword based on the first comparison result;

and the second query module is used for querying the keywords based on the priority of each keyword.

9. An electronic device, the electronic device comprising: a processor and a memory storing computer program instructions;

the processor, when executing the computer program instructions, implements a data query method as claimed in any one of claims 1-7 for application to a data center.

10. A computer readable storage medium, wherein computer program instructions are stored on the computer readable storage medium, which when executed by a processor, implement a data query method as claimed in any one of claims 1-7 for application to a data center.