CN115587115A - A database query optimization method and system - Google Patents

Abstract

The invention relates to the relevant field of database query, and discloses a database query optimization method and a system, wherein the database query optimization method comprises a retrieval space establishing module, a retrieval space mapping module, a characteristic association retrieval module and a data display verification module; by setting a physical optimization space independent of the database, the occupation of a data throughput channel of the database and the occupation of the operational capacity of the database in the retrieval process can be effectively reduced, and meanwhile, a multi-feature contact ratio retrieval method for performing characteristic scattering on the data objects is performed.

Description

A database query optimization method and system

technical field

The invention relates to the related field of database query, in particular to a database query optimization method and system.

Background technique

In the database field, the query capability of data in the database is one of the important items to measure the database. In the process of data query, the efficiency of data query is too low, which will lead to poor feedback response of the database as a whole, and it is difficult to satisfy the user's requirements for the database. The demand for fast query and acquisition of data content; at the same time, the data throughput of the database and the occupation of database computing power during data query will also affect the user experience feedback during the data query process, as well as the healthy consumption rate of the database.

Most of the data query methods in the prior art use the "and" and "or" relationships of multiple entries of the user to perform non-difference edge query comparisons on the database, which takes up a lot of data throughput and computing power while retrieving data content The method will lead to the problem that when the entry is offset, after the combination of multiple entries, the query result will be offset and the content of the required data cannot be correctly queried.

Contents of the invention

The purpose of the present invention is to provide a database query optimization method and system to solve the problems raised in the above-mentioned background technology.

To achieve the above object, the present invention provides the following technical solutions:

A database query optimization system, comprising:

The retrieval space building module is used to construct a physical optimization space for retrieval, the physical optimization space includes an optimized storage unit and an optimized retrieval unit, the optimized storage unit is used for storing retrieval features, and the optimized retrieval unit is used for responding to user requests Data query instructions to traverse the optimization storage unit, the physical optimization space is communicatively connected to the database;

The retrieval space mapping module is used to establish a data pointing link corresponding to the data in the database and store it in the optimized storage unit, obtain the retrieval characteristics of the corresponding data in the database through the characteristic acquisition program, and combine the retrieval characteristics with the corresponding The corresponding data points to link binding, and merges the retrieval features with the same content, and the retrieval features include data title features, content features, and user mark features;

The feature association retrieval module is used to obtain data query instructions from users, the data query instructions include multiple sets of retrieval features, traverse the optimized storage unit in sequence based on the retrieval features, obtain multiple data pointing links, and pass The retrieval counter performs traversal response counting on the links pointed to by the data, and generates associated retrieval results;

The data display and verification module is configured to sort in descending order the several data-directed links in the associated search results based on the result of the traversal response count, and obtain part of the corresponding data in the database through the data-directed links to generate verification preview, outputting the verification preview and receiving query confirmation feedback from the user.

As a further solution of the present invention: the retrieval space mapping module includes:

A media feature acquisition module, configured to identify the media content through a preset media object recognition program, acquire the element content composition of the media image, and based on the match between the element content and the comparison element in the preset identification library The degree sets the feature ratio for the corresponding retrieval feature. Each comparison element includes multiple retrieval features. Different retrieval features of the same comparison element are used to distinguish different expressions. The feature ratio is used for traversal response counting When , the count coefficient is given.

As a further solution of the present invention: the feature association retrieval module includes:

An additional filtering unit, configured to receive additional query conditions from users, and filter the data pointing links based on the additional query conditions, the additional query conditions are independent of the retrieval features and act on each of the data Pointing to links and database data, the additional query conditions include time information, file upload object, file type, and file data volume.

As a further solution of the present invention: it also includes a feature fuzzy module, and the feature fuzzy module specifically includes:

The vocabulary fuzzy unit is used to fuzz the vocabulary of the retrieval feature, obtain the retrieval feature similar to the text expression of the retrieval feature as a fuzzy retrieval feature, and perform fuzzy retrieval on the basis of the overlap between the text expression and the retrieval feature. The feature assigns the proportion of the feature;

The meaning fuzzy unit is used to fuzzy the meaning of the retrieval feature, obtain the retrieval feature similar to the text expression of the retrieval feature as a fuzzy retrieval feature, and perform fuzzy retrieval on the fuzzy retrieval feature based on a preset word meaning fuzzy grade library The assignment of feature proportions is carried out, and the word meaning fuzzy grade library includes a plurality of similar vocabulary storage spaces corresponding to different feature proportions.

As a further solution of the present invention: it also includes an object association module;

The object association module is used to establish the retrieval feature association tree of different users based on the retrieval preferences of different users and the final result of the query confirmation feedback, and the retrieval feature association tree is used to indicate that when a user searches through a certain retrieval feature, Other users that may be included in the retrieved object are not entered to retrieve the association between the features.

The embodiment of the present invention aims to provide a database query optimization method, comprising steps:

Construct a physical optimization space for retrieval, the physical optimization space includes an optimized storage unit and an optimized retrieval unit, the optimized storage unit is used to store retrieval features, and the optimized retrieval unit is used to respond to data query instructions from users to traverse the optimized storage unit, the physical optimization space is communicatively connected to the database;

Establishing a data pointing link corresponding to the data in the database and storing it in the optimized storage unit, obtaining the retrieval feature of the corresponding data in the database through a feature acquisition program, and linking the retrieval feature with the corresponding data pointing link Binding, and merging the retrieval features with the same content, the retrieval features include data title features, content features and user mark features;

Obtaining a data query instruction from the user, the data query instruction includes multiple sets of retrieval features, sequentially traversing the optimized storage unit based on the retrieval features, obtaining multiple data pointing links, and pointing to the data through the retrieval counter Links traverse the response count and generate associated retrieval results;

Based on the result of the traversal response counting, sort the data pointing links in the associated retrieval results in descending order, and obtain part of the corresponding data in the database through the data pointing links to generate a verification preview, and output the verification preview And receive query confirmation feedback from the user.

As a further solution of the present invention: the step of acquiring the retrieval features of the corresponding data in the database through the feature acquisition program includes:

Recognize the media content through a preset media object recognition program, obtain the composition of the element content of the media image, and compare the corresponding retrieval features based on the degree of conformity between the element content and the comparison elements in the preset recognition library Set feature proportions, each of the comparison elements includes multiple retrieval features, different retrieval features of the same comparison element are used to distinguish different expressions, and the feature proportions are used to assign counting coefficients when counting traversal responses.

As a further solution of the present invention: also include additional retrieval steps:

receiving additional query conditions from the user, and filtering the data-directed links based on the additional query conditions, the additional query conditions are independent of the retrieval feature and act on each of the data-directed links and database data, The additional query conditions include time information, file upload object, file type and file data volume.

As a further solution of the present invention: also include steps:

Vocabulary fuzzing is performed on the retrieval feature, and the retrieval feature similar to the text expression of the retrieval feature is obtained as a fuzzy retrieval feature, and the feature proportion of the fuzzy retrieval feature is calculated based on the coincidence degree between the text expression and the retrieval feature assignment;

Fuzzy the word meaning of the retrieval feature, obtain the retrieval feature similar to the text expression of the retrieval feature as the fuzzy retrieval feature, and assign the feature proportion to the fuzzy retrieval feature based on the preset word meaning fuzzy grade library , the word sense fuzzy grade library includes a plurality of similar vocabulary storage spaces respectively corresponding to different feature proportions.

As a further solution of the present invention: also include steps:

Based on the retrieval preferences of different users and the final result of the query confirmation feedback, the retrieval feature association tree of different users is established. The retrieval feature association tree is used to represent other users that may be included in the retrieval object when the user searches through a certain retrieval feature Not entered to retrieve associations between features.

Compared with the prior art, the beneficial effect of the present invention is that by setting a physical optimization space independent of the database, the occupation of the database data throughput channel and the calculation capacity of the database can be effectively reduced during the retrieval process, and at the same time, the data The multi-feature coincidence degree retrieval method of characterization and dispersal of objects, based on feature merging, can greatly reduce the amount of retrieval data in the retrieval process, improve retrieval efficiency, and can obtain a large number of feature matching data objects in a short time and combined screening.

Description of drawings

Figure 1 is a block diagram of a database query optimization system.

Fig. 2 is a block diagram of a feature fuzzy module in a database query optimization system.

Fig. 3 is a flowchart of a database query optimization method.

detailed description

In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

The specific implementation of the present invention will be described in detail below in conjunction with specific embodiments.

As shown in Figure 1, a database query optimization system provided by an embodiment of the present invention includes:

The retrieval space building module 100 is used to construct a physical optimization space for retrieval, and the physical optimization space includes an optimized storage unit and an optimized retrieval unit, the optimized storage unit is used to store retrieval features, and the optimized retrieval unit is used to respond to requests from users The data query instructions are used to traverse the optimization storage unit, and the physical optimization space is communicatively connected to the database.

The retrieval space mapping module 300 is used to establish a data pointing link corresponding to the data in the database and store it in the optimized storage unit, obtain the retrieval feature of the corresponding data in the database through the feature acquisition program, and combine the retrieval feature with the The corresponding data points to link binding, and the retrieval features with the same content are combined, and the retrieval features include data title features, content features, and user mark features.

The feature association retrieval module 500 is used to obtain data query instructions from users, the data query instructions include multiple sets of retrieval features, and sequentially traverse the optimized storage unit based on the retrieval features to obtain multiple data pointing links, and The search counter counts the traversal responses of the links pointed to by the data to generate an associated search result.

The data display verification module 700 is configured to sort in descending order the several data-directed links in the associated search results based on the result of the traversal response count, and obtain part of the content of the corresponding data in the database through the data-directed links to generate Verifying the preview, outputting the verification preview and receiving query confirmation feedback from the user.

In this embodiment, a data query optimization system is provided. By setting a physical optimization space independent of the database, it can effectively reduce the occupancy of the database data throughput channel and the occupancy of the database computing capacity during the retrieval process. The multi-feature coincidence degree retrieval method of characterization and dispersal of data objects, based on feature merging, can greatly reduce the amount of retrieval data in the retrieval process, improve retrieval efficiency, and achieve a large amount of feature matching data in a short time Objects are combined and screened; specifically, a physical optimization space paralleled and connected to the database is established, and when new data is stored in the database, it is searched for features (data features, such as the keywords of the title, the content keys of the data ontology) Words or high-frequency vocabulary, etc.), establish a data pointing link with the data link in the database and bind it to each feature, and at the same time merge the feature with the same feature in the physical optimization space, so that when searching, When the user enters a retrieval feature, multiple data-pointing links can be obtained based on the retrieval feature. When the user enters multiple retrieval keywords, a data-pointing link will be read multiple times. In this case, take The method of counting data pointing links, so that based on the search keywords entered by the user, it can be known that a certain data pointing link has been read the most times, and based on this, the output of the query and retrieval content can be obtained through the database when outputting part of the data content Previewing is performed to facilitate user confirmation, which intersects with the "and or" logical retrieval method when multiple keywords are juxtaposed in the shared technology. This application does not directly retrieve data content, but conducts a data retrieval based on keyword retrieval. The search count mark can effectively avoid the problem that the existing "and or" retrieval logic causes the data retrieval results to shift due to more keywords during retrieval, and even the correct data content cannot be retrieved in the end. In this application, the retrieval keyword The superposition of , will only increase the accuracy of the retrieval count, and will not lead to a multiplied reduction of the retrieval results.

As another preferred embodiment of the present invention, the retrieval space mapping module 300 includes:

A media feature acquisition module, configured to identify the media content through a preset media object recognition program, acquire the element content composition of the media image, and based on the match between the element content and the comparison element in the preset identification library The degree sets the feature ratio for the corresponding retrieval feature. Each comparison element includes multiple retrieval features. Different retrieval features of the same comparison element are used to distinguish different expressions. The feature ratio is used for traversal response counting When , the count coefficient is given.

In this embodiment, the media feature acquisition module is added to the retrieval space mapping module 300, which is set depending on the data type, because the data of the media type (here mainly refers to image media and video media, wherein video media can be viewed as Different from basic text and other types of data content, its retrieval characteristics (that is, the keywords of the content) can be uncertain. For the same image element, the expression of the keywords can be multiple At the same time, the expressions of similar elements may be relatively similar, so special content element identification and keyword extraction are required, and each element corresponds to multiple keywords, and different and similar expressions should also be set with certain features. The ratio is used to express the degree of overlap between the two, and is used for multiplication of coefficients during query and retrieval to improve the credibility of the data generated during the counting process.

As another preferred embodiment of the present invention, the feature association retrieval module 500 includes:

An additional filtering unit, configured to receive additional query conditions from users, and filter the data pointing links based on the additional query conditions, the additional query conditions are independent of the retrieval features and act on each of the data Pointing to links and database data, the additional query conditions include time information, file upload object, file type, and file data volume.

In this embodiment, the additional screening unit here can narrow the scope of retrieval by setting additional query conditions, such as setting the time range of retrieval data objects, which can greatly reduce the amount of retrieval data, and can also effectively improve the success rate of retrieval .

As shown in FIG. 2, as another preferred embodiment of the present invention, a feature fuzzy module 900 is also included, and the feature fuzzy module 900 specifically includes:

The vocabulary fuzzing unit 901 is used to perform vocabulary fuzzing on the retrieval feature, obtain the retrieval feature similar to the text expression of the retrieval feature as a fuzzy retrieval feature, and fuzzy the fuzzy retrieval feature based on the degree of coincidence between the text expression and the retrieval feature. Retrieve features to assign the proportion of features.

The word meaning fuzzy unit 902 is used to fuzzy the meaning of the retrieval feature, obtain the retrieval feature similar to the text expression of the retrieval feature as a fuzzy retrieval feature, and perform fuzzy retrieval on the basis of the preset word meaning fuzzy grade library The feature assigns the feature ratio, and the word meaning fuzzy hierarchy includes a plurality of similar vocabulary storage spaces corresponding to different feature ratios.

In this embodiment, the function of the feature fuzzy module 900 is to perform fuzzy association on the vocabulary input by the user during the retrieval process, which can be used to expand the retrieval range when the user has a wrong or inaccurate memory of the content of the data to be retrieved. Improve the success rate of retrieving the corresponding content. Of course, when the user cannot retrieve the corresponding content, this module will be opened based on needs. Among them, because the user's wrong expression may include similar text content and similar meaning of the keyword, it includes vocabulary Fuzzy unit 901 and word meaning fuzzy unit 902 .

As another preferred embodiment of the present invention, it also includes an object association module;

The object association module is used to establish the retrieval feature association tree of different users based on the retrieval preferences of different users and the final result of the query confirmation feedback, and the retrieval feature association tree is used to indicate that when a user searches through a certain retrieval feature, Other users that may be included in the retrieved object are not entered to retrieve the association between the features.

In this embodiment, the object association module is set for different users. According to the user's search and query habits, an association tree of search keywords belonging to the user can be established, which can be used to improve the system association fuzziness in the search and query process. accuracy.

As shown in Figure 3, the present invention also provides a kind of database query optimization method, and it comprises steps:

S200, constructing a physical optimization space for retrieval, the physical optimization space includes an optimized storage unit and an optimized retrieval unit, the optimized storage unit is used to store retrieval features, and the optimized retrieval unit is used to respond to data query instructions from users to traverse An optimized storage unit, the physically optimized space is communicatively connected to the database.

S400, establish a data pointing link corresponding to the data in the database and store it in the optimized storage unit, obtain the retrieval feature of the corresponding data in the database through the feature acquisition program, and associate the retrieval feature with the corresponding data Point to link binding, and merge the retrieval features with the same content, the retrieval features include data title features, content features and user mark features.

S600. Obtain a data query instruction from the user, the data query instruction includes multiple sets of retrieval features, sequentially traverse the optimized storage unit based on the retrieval features, obtain multiple data pointing links, and use the retrieval counter to search the optimized storage unit The data points to the link to traverse the response count and generate the associated retrieval result.

S800. Arrange in descending order the several data-pointing links in the associated search results based on the result of the traversal response counting, and obtain part of the corresponding data in the database through the data-pointing links to generate a verification preview, and output the Validate previews and receive query confirmation feedback from users.

As another preferred embodiment of the present invention, the step of acquiring the retrieval features of the corresponding data in the database through the feature acquisition program includes:

Recognize the media content through a preset media object recognition program, obtain the composition of the element content of the media image, and compare the corresponding retrieval features based on the degree of conformity between the element content and the comparison elements in the preset recognition library Set feature proportions, each of the comparison elements includes multiple retrieval features, different retrieval features of the same comparison element are used to distinguish different expressions, and the feature proportions are used to assign counting coefficients when counting traversal responses.

As another preferred embodiment of the present invention, the step of generating associated retrieval results further includes an additional retrieval step:

receiving additional query conditions from the user, and filtering the data-directed links based on the additional query conditions, the additional query conditions are independent of the retrieval feature and act on each of the data-directed links and database data, The additional query conditions include time information, file upload object, file type and file data volume.

As another preferred embodiment of the present invention, it also includes the steps of:

Vocabulary fuzzing is performed on the retrieval feature, and the retrieval feature similar to the text expression of the retrieval feature is obtained as a fuzzy retrieval feature, and the feature proportion of the fuzzy retrieval feature is calculated based on the coincidence degree between the text expression and the retrieval feature assignment.

Fuzzy the word meaning of the retrieval feature, obtain the retrieval feature similar to the text expression of the retrieval feature as the fuzzy retrieval feature, and assign the feature proportion to the fuzzy retrieval feature based on the preset word meaning fuzzy grade library , the word sense fuzzy grade library includes a plurality of similar vocabulary storage spaces respectively corresponding to different feature proportions.

As another preferred embodiment of the present invention, it also includes the steps of:

Based on the retrieval preferences of different users and the final result of the query confirmation feedback, the retrieval feature association tree of different users is established. The retrieval feature association tree is used to represent other users that may be included in the retrieval object when the user searches through a certain retrieval feature Not entered to retrieve associations between features.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be realized through computer programs to instruct related hardware, and the programs can be stored in a non-volatile computer-readable storage medium When the program is executed, it may include the processes of the embodiments of the above-mentioned methods. Wherein, any references to memory, storage, database or other media used in the various embodiments provided in the present application may include non-volatile and/or volatile memory. Nonvolatile memory can include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Chain Synchlink DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

Other embodiments of the present disclosure will readily occur to those skilled in the art from consideration of the disclosure at the specification and examples. This application is intended to cover any modification, use or adaptation of the present disclosure, and these modifications, uses or adaptations follow the general principles of the present disclosure and include common knowledge or conventional technical means in the technical field not disclosed in the present disclosure . The specification and examples are to be considered exemplary only, with the true scope and spirit of the disclosure indicated by the appended claims.

It should be understood that the present disclosure is not limited to the precise constructions which have been described above and shown in the drawings, and various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims (10)

1. A database query optimization system, comprising:

the system comprises a retrieval space establishing module, a database searching module and a searching module, wherein the retrieval space establishing module is used for establishing a physical optimized space for retrieval, the physical optimized space comprises an optimized storage unit and an optimized retrieval unit, the optimized storage unit is used for storing retrieval characteristics, the optimized retrieval unit is used for responding to a data query instruction from a user to traverse the optimized storage unit, and the physical optimized space is in communication connection with the database;

the retrieval space mapping module is used for establishing data pointing links which are in one-to-one corresponding connection with data in a database and storing the data pointing links in the optimized storage unit, acquiring retrieval characteristics of corresponding data in the database through a characteristic acquisition program, binding the retrieval characteristics with the corresponding data pointing links, and merging the retrieval characteristics with the same content, wherein the retrieval characteristics comprise title characteristics, content characteristics and user mark characteristics of the data;

the characteristic correlation retrieval module is used for acquiring a data query instruction from a user, wherein the data query instruction comprises a plurality of groups of retrieval characteristics, traversing the optimized storage unit in sequence based on the retrieval characteristics to acquire a plurality of data pointing links, and performing traversal response counting on the data pointing links through a retrieval counter to generate a correlation retrieval result;

and the data display verification module is used for performing descending order arrangement on a plurality of data pointing links in the associated retrieval result based on the result of the traversal response counting, acquiring partial content of corresponding data in a database through the data pointing links to generate verification preview, outputting the verification preview and receiving query confirmation feedback from a user.

2. The database query optimization system of claim 1, wherein the search space mapping module comprises:

the media feature acquisition module is used for identifying the media content through a preset media object identification program, acquiring element content constitution of the media image, and setting feature ratio for corresponding retrieval features based on the matching degree of the element content and comparison elements in a preset identification library, wherein each comparison element comprises a plurality of retrieval features, different retrieval features of the same comparison element are used for distinguishing different expression modes, and the feature ratio is used for endowing a counting coefficient when traversing response counting is carried out.

3. The database query optimization system of claim 2, wherein the feature association retrieval module comprises:

and the additional screening unit is used for receiving an additional query condition from a user and screening the data pointing links based on the additional query condition, wherein the additional query condition is independent of the retrieval characteristics and acts on each data pointing link and the database data, and the additional query condition comprises time information, a file uploading object, a file type and a file data volume.

4. The database query optimization system according to claim 3, further comprising a feature fuzzy module, wherein the feature fuzzy module specifically comprises:

the word fuzzy unit is used for carrying out word fuzzy on the retrieval characteristics, acquiring the retrieval characteristics close to the character expression of the retrieval characteristics as fuzzy retrieval characteristics, and carrying out characteristic proportion assignment on the fuzzy retrieval characteristics based on the coincidence degree of the character expression and the retrieval characteristics;

and the word meaning fuzzy unit is used for carrying out word meaning fuzzy on the retrieval characteristics, acquiring the retrieval characteristics which are close to the character expression of the retrieval characteristics as fuzzy retrieval characteristics, and carrying out characteristic ratio assignment on the fuzzy retrieval characteristics based on a preset word meaning fuzzy level library, wherein the word meaning fuzzy level library comprises a plurality of similar vocabulary storage spaces respectively corresponding to different characteristic ratios.

5. The database query optimization system of claim 1, further comprising an object association module;

the object association module is used for establishing retrieval feature association trees of different users based on retrieval preferences of the different users and final results of query confirmation feedback, and the retrieval feature association trees are used for representing the association between retrieval features which are not input by other users possibly contained in the retrieved object when the user retrieves through a certain retrieval feature.

6. A method for optimizing a database query, comprising the steps of:

constructing a retrieved physical optimization space, wherein the physical optimization space comprises an optimization storage unit and an optimization retrieval unit, the optimization storage unit is used for storing retrieval characteristics, the optimization retrieval unit is used for responding to a data query instruction from a user to traverse the optimization storage unit, and the physical optimization space is in communication connection with a database;

establishing data pointing links in one-to-one corresponding connection with data in a database and storing the data pointing links in the optimized storage unit, acquiring retrieval characteristics of corresponding data in the database through a characteristic acquisition program, binding the retrieval characteristics with the corresponding data pointing links, and merging the retrieval characteristics with the same content, wherein the retrieval characteristics comprise a title characteristic, a content characteristic and a user mark characteristic of the data;

acquiring a data query instruction from a user, wherein the data query instruction comprises a plurality of groups of retrieval characteristics, traversing the optimized storage unit in sequence based on the retrieval characteristics to acquire a plurality of data pointing links, and traversing response counting is performed on the data pointing links through a retrieval counter to generate an associated retrieval result;

and performing descending order arrangement on a plurality of data pointing links in the associated retrieval result based on the result of the traversal response count, acquiring partial content of corresponding data in a database through the data pointing links to generate a verification preview, outputting the verification preview and receiving query confirmation feedback from a user.

7. The method according to claim 6, wherein the step of obtaining the search features of the corresponding data in the database by the feature obtaining program comprises:

the media content is identified through a preset media object identification program, the element content constitution of the media image is obtained, feature proportion is set for corresponding retrieval features based on the matching degree of the element content and comparison elements in a preset identification library, each comparison element comprises a plurality of retrieval features, different retrieval features of the same comparison element are used for distinguishing different expression modes, and the feature proportion is used for endowing a counting coefficient when traversing response counting is carried out.

8. The database query optimization method of claim 7, further comprising the additional retrieval step of:

receiving an additional query condition from a user, and screening the data pointing links based on the additional query condition, wherein the additional query condition is independent of the retrieval characteristics and acts on each data pointing link and database data, and the additional query condition comprises time information, a file uploading object, a file type and a file data volume.

9. The database query optimization method according to claim 8, further comprising the steps of:

carrying out vocabulary fuzzy on the retrieval characteristics, acquiring the retrieval characteristics close to the character expression of the retrieval characteristics as fuzzy retrieval characteristics, and carrying out characteristic ratio assignment on the fuzzy retrieval characteristics based on the coincidence degree of the character expression and the retrieval characteristics;

and carrying out word sense fuzzy on the retrieval characteristics, acquiring the retrieval characteristics close to the character expression of the retrieval characteristics as fuzzy retrieval characteristics, and carrying out characteristic ratio assignment on the fuzzy retrieval characteristics based on a preset word sense fuzzy level library, wherein the word sense fuzzy level library comprises a plurality of similar vocabulary storage spaces respectively corresponding to different characteristic ratios.

10. The database query optimization method according to claim 6, further comprising the steps of:

and establishing a retrieval feature association tree of different users based on the retrieval preference of different users and the final result of query confirmation feedback, wherein the retrieval feature association tree is used for representing the association between the retrieval features which are not input by other users possibly contained in the object to be retrieved when the user retrieves through a certain retrieval feature.

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