CN115563189A - Mass data query method based on data mining technology - Google Patents
Mass data query method based on data mining technology Download PDFInfo
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- CN115563189A CN115563189A CN202211292179.3A CN202211292179A CN115563189A CN 115563189 A CN115563189 A CN 115563189A CN 202211292179 A CN202211292179 A CN 202211292179A CN 115563189 A CN115563189 A CN 115563189A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2465—Query processing support for facilitating data mining operations in structured databases
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2228—Indexing structures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/23—Updating
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/248—Presentation of query results
Abstract
The invention relates to the technical field of data query, and particularly discloses a mass data query method based on a data mining technology, wherein S1: a user logs in and registers a data query system; s2: a user inputs a query condition in the system; s3: the system pre-judges the data to be inquired of the user and puts the pre-judged data out of the database for standby; s4: according to the query condition finally input by the user, the system preferentially extracts the query data from the pre-judged data for displaying; s5: if the pre-judged data does not contain query data meeting the query conditions of the user, the system extracts the query data from the database for display; s6: and the user selects the required data independently. According to the scheme, the required query data of the user can be judged in advance according to the query conditions in the input of the user, the related retrieval habits, the retrieval preferences, the user identity information and the like, more accurate and high-quality query data storage is provided for the later-stage all-round retrieval of the user, the system data query efficiency is improved, and the user experience is improved.
Description
Technical Field
The invention relates to the technical field of data query, in particular to a mass data query method based on a data mining technology.
Background
The mass data refers to huge and vast data. At present, most of the applications are connected with a database, and expected data results are obtained through operations such as query. When a certain amount of data is reached, a plurality of query conditions are met, or a plurality of persons simultaneously query online, the query statistics from the database usually takes a long time, so that the query efficiency is low, a high time cost is caused for a query user, and the user experience is poor.
Disclosure of Invention
The invention aims to provide a mass data query method based on a data mining technology, so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a mass data query method based on a data mining technology comprises the following specific steps:
s1: a user logs in and registers a data query system;
s2: a user inputs a query condition in the system;
s3: the system pre-judges the data to be inquired of the user according to the inquiry condition input by the user and the registration information of the user, and extracts the pre-judged data from a database for later use;
s4: according to the query condition finally input by the user, the system preferentially extracts the query data meeting the query condition of the user from the proposed standby pre-judgment data to a query interface of the system for displaying;
s5: if the pre-judgment data does not contain query data meeting the query conditions of the user, the system extracts the query data meeting the query conditions of the user from the database and displays the query data on a query interface of the system;
s6: and the user can independently select the required data according to the query data displayed on the query interface.
As a preferred scheme of the present invention, the data query system includes a database, the database includes an entry module and a storage module, the entry module is used for data entry and update of the database, and the storage module is used for classified storage and processing of data in the database according to an entered data attribute.
As a preferred scheme of the present invention, the storage module includes a keyword storage unit, a user attribute storage unit, and an input attribute storage unit, where the keyword storage unit is configured to store data in a classified manner according to a keyword in the input data, the user attribute storage unit is configured to store data in a classified manner according to a user attribute of a corresponding user in the system, and the input attribute storage unit is configured to store data in a classified manner according to input data attribute information.
As a preferred embodiment of the present invention, the user attribute includes the relevant information including age, occupation, location and hobbies, which is filled in by the user in the account registered in the query system.
As a preferred scheme of the present invention, the data query system includes an input module and a fast search module, the input module is used for a query staff to input query conditions to be queried into the system, and the fast search module is used for searching in a database according to the attribute category of the final query condition of the query staff and providing search data meeting the query conditions.
As a preferred scheme of the present invention, the data query system further includes a pre-judging module, a pre-retrieving module, and a pre-storing module, wherein the pre-judging module is configured to pre-judge relevant data to be queried according to login information of a query person and retrieval information in input, the pre-retrieving module is configured to perform a pre-retrieving operation in the database according to a pre-judging result of the pre-judging module, and bring the pre-retrieved data system out of the database to the pre-storing module for standby, and the pre-storing module is configured to store pre-retrieved data brought out by the pre-retrieving module.
As a preferred embodiment of the present invention, the fast retrieving module is connected to the pre-storing module, and the fast retrieving module preferentially retrieves and provides the retrieved data meeting the query condition from the pre-storing module according to the attribute category of the final query condition of the querying person.
As a preferred scheme of the present invention, the data query system further includes a user analysis module, and the user analysis module is configured to analyze, process, and integrate the relevant query information and data of the user, so as to provide a more customized data query service for a specific logged-in user when the user wants to use the data query system at a later stage.
As a preferred scheme of the present invention, the user analysis module includes a history tracing unit, a query analysis unit, and a query data processing unit, the history tracing unit is configured to record and trace query data of a user, the query analysis unit is configured to analyze the user query data in the history tracing unit, and further analyze a relevant user search attribute, and the query data processing unit is configured to store the search attribute of the corresponding user analyzed by the query analysis unit, and send the data to the pre-judging module for cooperative use.
As a preferable aspect of the present invention, the user search attribute includes related information including search habits and search preferences of the login user.
Compared with the prior art, the invention has the beneficial effects that:
aiming at the technical problem that the existing mass data query is low in data efficiency, the scheme adds a search pre-judging function in the data query system, so that the data query system can pre-judge the required query data of the user according to the query conditions in the input of the user, the related search habits, the search preferences, the user identity information and the like of the user, more accurate and high-quality query data storage is provided for the later-stage comprehensive search of the user, the data query efficiency of the system is improved, and the experience of the user is improved.
Drawings
FIG. 1 is a flow chart of a mass data query method of the present invention;
FIG. 2 is a detailed architecture diagram of the data query system of the present invention.
In the figure: 1. a data query system; 11. an input module; 12. a quick retrieval module; 13. a prejudgment module; 14. a pre-retrieval module; 15. a pre-storage module; 16. a user analysis module; 161. a history tracing unit; 162. a query analysis unit; 163. a query data processing unit; 2. a database; 21. a recording module; 22. a storage module; 221. a keyword storage unit; 222. a user attribute storage unit; 223. an input attribute storage unit.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, the present invention provides a technical solution: a mass data query method based on a data mining technology comprises the following specific steps:
s1: a user logs in and registers the data query system 1;
s2: the user inputs the query condition in an input module 11 in the system;
s3: the system pre-judges relevant data which the user may need to inquire through the pre-judging module 13 according to the inquiry condition (through an input method, an information attribute in input and the like) input by the user in the input module 11 and the retrieval attribute of the corresponding user stored by the inquiry data processing unit 163, performs pre-retrieval operation in the database 2 according to the pre-judging result through the pre-retrieving module 14, and puts the pre-retrieved data system out of the database 2 to the pre-storing module 15 for standby;
s4: according to the query condition finally input by the user, the system preferentially extracts the query data of the user from the standby prejudged data in the pre-storage module 15 to a query interface of the system for displaying;
s5: if the pre-judgment data does not contain query data meeting the query conditions of the user, the system extracts the query data meeting the query conditions of the user from the database 2 and displays the query data on a query interface of the system;
s6: the user can independently select required data according to the query data displayed by the query interface;
s7: the system traces back the query conditions of the user and the required data selected by the user according to the history tracing back unit 162, analyzes and processes the data information through the query analysis unit, and stores the analysis processing result to the query data processing unit 163 for later use in cooperation with the pre-judging module 13.
The data query system 1 in the above steps includes a database 2, the database 2 includes an entry module 21 and a storage module 22, the entry module 21 is used for data entry and update of the database 2, and the storage module 22 is used for classified storage and processing of data in the database 2 according to the entered data attribute.
The storage module 22 includes a keyword storage unit 221, a user attribute storage unit 222, and an input attribute storage unit 223, where the keyword storage unit 221 is used to store data by classification according to a keyword in the input data, the user attribute storage unit 222 is used to store data by classification according to a user attribute of a corresponding user in the system, and the input attribute storage unit 223 is used to store data by classification according to input data attribute information.
The user attributes comprise relevant information including age, occupation, region and hobbies, which are filled in by the user in the account registered in the query system.
The data query system 1 in the above steps includes an input module 11 and a fast retrieval module 12, where the input module 11 is used for a query staff to input query conditions to be queried into the system, and the fast retrieval module 12 is used for retrieving and providing retrieval data meeting the query conditions in the database 2 according to the attribute category of the final query conditions of the query staff.
The data query system 1 further comprises a pre-judging module 13, a pre-retrieving module 14 and a pre-storing module 15, wherein the pre-judging module 13 is used for pre-judging relevant data to be queried according to login information of a query worker and retrieval information in input, the pre-retrieving module 14 is used for performing pre-retrieving operation in the database 2 according to a pre-judging result of the pre-judging module 13, and the pre-retrieved data system is put out from the database 2 to the pre-storing module 15 for standby, and the pre-storing module 15 is used for storing the pre-retrieved data put out by the pre-retrieving module 14.
The fast retrieval module 12 is connected to the pre-storage module 22, and the fast retrieval module 12 preferentially retrieves and provides the retrieval data meeting the query condition from the pre-storage module 22 according to the attribute category of the final query condition of the querying person.
The data query system 1 further includes a user analysis module 16, and the user analysis module 16 is configured to analyze, process and integrate the relevant query information and data of the user.
The user analysis module 16 includes a history tracing unit 161, a query analysis unit 162, and a query data processing unit 163, the history tracing unit 161 is configured to record and trace query data of a user, the query analysis unit 162 is configured to analyze the user query data in the history tracing unit 161, and further analyze a relevant user search attribute, the query data processing unit 163 is configured to store the search attribute of the corresponding user analyzed by the query analysis unit 162, the user search attribute includes relevant information including a search habit and a search preference of a logged-in user, and the analyzed data is sent to the anticipation module 13 for cooperative use.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. A mass data query method based on data mining technology is characterized in that: the method comprises the following specific steps:
s1: a user logs in and registers a data query system (1);
s2: a user inputs a query condition in the system;
s3: the system pre-judges the data to be inquired of the user according to the inquiry condition input by the user and the registration information of the user, and puts the pre-judged data out of the database (2) for later use;
s4: according to the query condition finally input by the user, the system preferentially extracts the query data meeting the query condition of the user from the proposed standby pre-judgment data to a query interface of the system for displaying;
s5: if the predicted data does not contain query data meeting the query condition of the user, the system extracts the query data meeting the query condition of the user from the database (2) to a query interface of the system for display;
s6: and the user can independently select the required data according to the query data displayed on the query interface.
2. The mass data query method based on the data mining technology as claimed in claim 1, wherein: the data query system (1) comprises a database (2), the database (2) comprises an entry module (21) and a storage module (22), the entry module (21) is used for data entry and update of the database (2), and the storage module (22) is used for classified storage and processing of data in the database (2) according to entered data attributes.
3. The mass data query method based on the data mining technology as claimed in claim 2, wherein: the storage module (22) comprises a keyword storage unit (221), a user attribute storage unit (222) and an input attribute storage unit (223), wherein the keyword storage unit (221) is used for classifying and storing data according to keywords in the input data, the user attribute storage unit (222) is used for classifying and storing according to user attributes of corresponding users in the system, and the input attribute storage unit (223) is used for classifying and storing data according to input data attribute information.
4. The mass data query method based on the data mining technology as claimed in claim 3, wherein: the user attributes comprise relevant information including age, occupation, region and hobbies, which are filled in the account registered in the query system by the user.
5. The mass data query method based on the data mining technology as claimed in claim 1, wherein: the data query system (1) comprises an input module (11) and a quick retrieval module (12), wherein the input module (11) is used for a query staff to input query conditions to be queried into the system, and the quick retrieval module (12) is used for retrieving and providing retrieval data meeting the query conditions in the database (2) according to the attribute category of the final query conditions of the query staff.
6. The mass data query method based on the data mining technology as claimed in claim 1, wherein: the data query system (1) further comprises a pre-judging module (13), a pre-retrieving module (14) and a pre-storing module (15), wherein the pre-judging module (13) is used for pre-judging relevant data to be queried according to login information and retrieval information in input of a query worker, the pre-retrieving module (14) is used for performing pre-retrieving operation in the database (2) according to a pre-judging result of the pre-judging module (13) and extracting a pre-retrieved data system from the database (2) to the pre-storing module (15) for standby, and the pre-storing module (15) is used for storing the pre-retrieved data extracted by the pre-retrieving module (14).
7. The mass data query method based on the data mining technology as claimed in claim 5, wherein: the quick retrieval module (12) is connected with the pre-storage module (22), and the quick retrieval module (12) preferentially retrieves and provides retrieval data meeting the query conditions from the pre-storage module (22) according to the attribute category of the final query condition of the inquirer.
8. The mass data query method based on the data mining technology as claimed in claim 1, wherein: the data query system (1) further comprises a user analysis module (16), and the user analysis module (16) is used for analyzing, processing and integrating the relevant query information and data of the user.
9. The mass data query method based on the data mining technology as claimed in claim 1, wherein: the user analysis module (16) comprises a history tracing unit (161), a query analysis unit (162) and a query data processing unit (163), wherein the history tracing unit (161) is used for recording and tracing query data of a user, the query analysis unit (162) is used for analyzing the user query data in the history tracing unit (161) and further analyzing related user retrieval attributes, and the query data processing unit (163) is used for storing the retrieval attributes of the corresponding user analyzed by the query analysis unit (162) and sending the data to the pre-judging module (13) for cooperative use.
10. The mass data query method based on the data mining technology as claimed in claim 9, wherein: the user retrieval attribute comprises relevant information including retrieval habits and retrieval preferences of login users.
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| CN115860925A (en) * | 2023-02-19 | 2023-03-28 | 广东德澳智慧医疗科技有限公司 | Intelligent data query and investment management system based on artificial intelligence liability |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115860925A (en) * | 2023-02-19 | 2023-03-28 | 广东德澳智慧医疗科技有限公司 | Intelligent data query and investment management system based on artificial intelligence liability |
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