CN115563189A - A Massive Data Query Method Based on Data Mining Technology - Google Patents

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

A Massive Data Query Method Based on Data Mining Technology

technical field

The invention relates to the technical field of data query, in particular to a massive data query method based on data mining technology.

Background technique

Massive data refers to huge, vast data. At present, most applications must be connected to the database, and the expected results of the data can be obtained through operations such as queries. When a certain amount of data is reached, many query conditions are met, or multiple people query online at the same time, it usually takes a long time to query statistics from the database, resulting in low query efficiency, causing high time costs for query users, and causing users to The experience is poor.

Contents of the invention

The purpose of the present invention is to provide a massive data query method based on data mining technology, so as to solve the problems raised in the above-mentioned background technology.

In order to achieve the above object, the present invention provides the following technical solutions: a massive data query method based on data mining technology, comprising the following specific steps:

S1: User login and registration data query system;

S2: The user inputs query conditions in the system;

S3: The system predicts the user's data to be queried according to the query conditions entered by the user and the user's registration information, and puts the predicted data out of the database for backup;

S4: According to the query conditions finally input by the user, the system preferentially extracts the query data that meets the user's query conditions from the proposed spare pre-judgment data and displays them on the query interface of the system;

S5: If there is no query data that meets the user's query conditions in the predicted data, the system extracts the query data that meets the user's query conditions from the database and displays them on the query interface of the system;

S6: The user can independently select the required data according to the query data displayed on the query interface.

As a preferred solution of the present invention, the data query system includes a database, and 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 processing data in the database according to the entered data attributes Classified storage and processing.

As a preferred solution of the present invention, the storage module includes a keyword storage unit, a user attribute storage unit, and an input attribute storage unit, the keyword storage unit is used to classify and store data according to keywords in the input data, and the user attribute The storage unit is used for classifying and storing the user attributes of the corresponding users in the system, and the input attribute storage unit is used for classifying and storing the data according to the input data attribute information.

As a preferred solution of the present invention, the user attributes include relevant information including age, occupation, location, and hobbies that the user fills in the registered account in the query system.

As a preferred solution of the present invention, the data query system includes an input module and a fast retrieval module, the input module is used for the query personnel to input the query conditions to be queried into the system, and the fast retrieval module is used for the query according to the final query conditions of the query personnel The attribute categories are searched in the database, and the retrieved data that meets the query conditions are proposed.

As a preferred solution of the present invention, the data query system further includes a pre-judgment module, a pre-retrieval module, and a pre-storage module, and the pre-judgment module is used to predict the query required by the queryer according to his login information and input retrieval information The pre-retrieval module is used to perform pre-retrieval operations in the database according to the pre-judgment results of the pre-judgment module, and the pre-retrieved data system is proposed from the database to the pre-storage module for backup, and the pre-storage module is used to store the pre-storage The pre-retrieval data proposed by the retrieval module.

As a preferred solution of the present invention, the fast retrieval module is connected to the pre-storage module, and the fast retrieval module preferentially retrieves from the pre-storage module according to the attribute category of the queryer's final query condition, and proposes retrieval data that meets the query condition.

As a preferred solution of the present invention, the data query system also includes a user analysis module, which is used to analyze, process and integrate the relevant query information and data of the user, so as to facilitate the later use of the data by specific login users When querying the system, it provides more customized data query services.

As a preferred solution of the present invention, the user analysis module includes a history traceability unit, a query analysis unit and a query data processing unit, the history traceability unit is used to record and trace user query data, and the query analysis unit is used to analyze the history traceability unit Analyze the user query data in the system, and then analyze the relevant user retrieval attributes. The query data processing unit is used to store the corresponding user retrieval attributes analyzed by the query analysis unit, and send the data to the pre-judgment module for collaborative use.

As a preferred solution of the present invention, the user retrieval attributes include relevant information including retrieval habits and retrieval preferences of the logged-in user.

Compared with prior art, the beneficial effect of the present invention is:

The present invention provides a massive data query method based on data mining technology. This solution aims at the existing technical problem of low efficiency of massive data query data, and adds a retrieval and pre-judgment function in the data query system, so that it can The query conditions in the input, the user's relevant retrieval habits, retrieval preferences, user identity information, etc. are used to predict the query data required by the user, so as to provide more accurate and high-quality query data reserves for the later user's all-round retrieval, and improve the System data query efficiency improves user experience.

Description of drawings

Fig. 1 is the flowchart of massive data query method of the present invention;

FIG. 2 is a specific architecture diagram of the data query system of the present invention.

In the figure: 1. Data query system; 11. Input module; 12. Quick retrieval module; 13. Pre-judgment module; 14. Pre-retrieval module; 15. Pre-storage module; 16. User analysis module; 161. History tracing unit; 162. Query analysis unit; 163. Query data processing unit; 2. Database; 21. Input module; 22. Storage module; 221. Keyword storage unit; 222. User attribute storage unit; 223. Input attribute storage unit.

detailed description

The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

Please refer to Fig. 1-2, the present invention provides a kind of technical scheme: a kind of massive data query method based on data mining technology, comprises the following specific steps:

S1: user login, registration data query system 1;

S2: the user inputs query conditions in the input module 11 in the system;

S3: The system predicts the user's possible Relevant data that needs to be queried is carried out in the database 2 by the pre-retrieval module 14 according to the pre-judgment result, and the pre-retrieval data system is proposed to the pre-storage module 15 from the database 2 for standby;

S4: According to the query condition finally input by the user, the system preferentially extracts the user's query data from the spare pre-judgment data in the pre-storage module 15 to the query interface of the system for display;

S5: If there is no query data that meets the user's query conditions in the predicted data, the system extracts the query data that meets the user's query conditions from the database 2 and displays them on the query interface of the system;

S6: The user can independently select the required data according to the query data displayed on the query interface;

S7: The system traces back the query conditions of the user and the required data independently selected by the user according to the history tracing unit 162, analyzes and processes the above data information through the query analysis unit, and stores the analysis and processing results in the query data processing unit 163, For later use in coordination with the pre-judgment module 13.

The data query system 1 in the above-mentioned steps comprises a database 2, and 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 checking the data in the database 2 according to the data attributes entered. classified data storage and processing.

The storage module 22 includes a keyword storage unit 221, a user attribute storage unit 222, and an input attribute storage unit 223. The keyword storage unit 221 is used to classify and store data according to the keywords in the input data, and the user attribute storage unit 222 is used to store the data according to the keywords in the input data. The user attributes of corresponding users in the system are classified and stored, and the input attribute storage unit 223 is used to classify and store data according to the input data attribute information.

User attributes include relevant information including age, occupation, location, and hobbies that the user fills in the registered account in the query system.

The data query system 1 in the above-mentioned steps comprises an input module 11 and a quick retrieval module 12. The input module 11 is used for the query personnel to input the query conditions to be queried in the system, and the fast retrieval module 12 is used for according to the attributes of the query personnel's final query conditions. The categories are searched in the database 2, and the retrieved data that meet the query conditions are proposed.

The data query system 1 also includes a pre-judgment module 13, a pre-retrieval module 14, and a pre-storage module 15. The pre-judgment module 13 is used to predict the relevant data that needs to be queried according to the login information of the inquirer and the retrieval information in the input, and the pre-retrieval Module 14 is used to carry out pre-retrieval operation in database 2 according to the pre-judgment result of pre-judgment module 13, and puts the pre-retrieved data system from database 2 to pre-storage module 15 for standby, and pre-storage module 15 is used to store pre-storage The retrieval module 14 proposes pre-retrieval data.

The fast retrieval module 12 is connected with the pre-storage module 22, and the fast retrieval module 12 retrieves from the pre-storage module 22 according to the attribute category of the final query condition of the queryer, and proposes retrieval data that meets the query conditions.

The data query system 1 also includes a user analysis module 16 for analyzing, processing and integrating relevant query information and data of users.

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 used to record and trace user query data, and the query analysis unit 162 is used to query the user in the history tracing unit 161. The query data processing unit 163 is used to store the corresponding user’s retrieval attributes analyzed by the query analysis unit 162, and the user retrieval attributes include the login user’s retrieval habits and retrieval preferences. Relevant information and analyzed data are sent to the pre-judgment module 13 for collaborative use.

Although the embodiments of the present invention have been shown and described, those skilled in the art can understand that various changes, modifications and substitutions can be made to these embodiments without departing from the principle and spirit of the present invention. and modifications, the scope of the invention is defined by the appended claims and their equivalents.

Claims (10)

1. A massive data query method based on data mining technology, characterized in that: comprise the following concrete steps: S1: User login, registration data query system (1); S2: The user inputs query conditions in the system; S3: The system predicts the user's data to be queried according to the query conditions entered by the user and the user's registration information, and extracts the predicted data from the database (2) for backup; S4: According to the query conditions finally input by the user, the system preferentially extracts the query data that meets the user's query conditions from the proposed spare pre-judgment data and displays them on the query interface of the system; S5: If there is no query data that meets the user's query conditions in the predicted data, the system extracts the query data that meets the user's query conditions from the database (2) and displays them on the query interface of the system; S6: The user can independently select the required data according to the query data displayed on the query interface. 2. A massive data query method based on data mining technology according to claim 1, characterized in that: the data query system (1) includes a database (2), and the database (2) includes an entry module (21), The 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 classifying, storing and processing the data in the database (2) according to the attributes of the entered data. 3. A massive data query method based on data mining technology according to claim 2, characterized in that: the storage module (22) includes a keyword storage unit (221), a user attribute storage unit (222), an input The attribute storage unit (223), the keyword storage unit (221) is used to classify and store the data according to the keywords in the input data, and the user attribute storage unit (222) is used to classify and store the user attributes of the corresponding users in the system, The input attribute storage unit (223) is used for classifying and storing the data according to the input data attribute information. 4. A kind of mass data query method based on data mining technology according to claim 3, characterized in that: said user attributes include age, occupation, location, hobbies, etc. filled in by the user in the account number registered in the query system. related information in . 5. A massive data query method based on data mining technology according to claim 1, characterized in that: the data query system (1) includes an input module (11), a fast retrieval module (12), an input module ( 11) It is used for the query personnel to input the query conditions to be queried into the system, and the quick retrieval module (12) is used for searching in the database (2) according to the attribute category of the query personnel's final query conditions, and to propose retrieval data that meet the query conditions. 6. A massive data query method based on data mining technology according to claim 1, characterized in that: the data query system (1) also includes a pre-judgment module (13), a pre-retrieval module (14), a pre- The storage module (15), the pre-judgment module (13) is used to predict the relevant data that needs to be queried according to the queryer's login information and the input retrieval information, and the pre-retrieval module (14) is used to The pre-judgment results are pre-retrieved in the database (2), and the pre-retrieved data system is proposed from the database (2) to the pre-storage module (15) for backup, and the pre-storage module (15) is used to store the pre-retrieval Module (14) presents the pre-retrieval data. 7. A massive data query method based on data mining technology according to claim 5, characterized in that: the fast retrieval module (12) is connected to the pre-storage module (22), and the fast retrieval module (12) according to the query The attribute category of the final query condition of the personnel is preferentially retrieved from the pre-storage module (22), and the retrieval data meeting the query condition is proposed. 8. A massive data query method based on data mining technology according to claim 1, characterized in that: the data query system (1) further includes a user analysis module (16), which is used to Analyze, process and integrate relevant query information and data of users. 9. A massive data query method based on data mining technology according to claim 1, characterized in that: the user analysis module (16) includes a history tracing unit (161), a query analysis unit (162) and a query data The processing unit (163), the history tracing unit (161) is used to record and trace the query data of the user, and the query analysis unit (162) is used to analyze the user query data in the history tracing unit (161), and then analyze the relevant The user retrieval attribute, the query data processing unit (163) is used to store the retrieval attribute of the corresponding user analyzed by the query analysis unit (162), and send the data to the pre-judgment module (13) for collaborative use. 10. A massive data query method based on data mining technology according to claim 9, characterized in that: said user retrieval attributes include relevant information including retrieval habits and retrieval preferences of logged-in users.

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