CN114397967A - Automatic association method for auxiliary input keywords of database - Google Patents
Automatic association method for auxiliary input keywords of database Download PDFInfo
- Publication number
- CN114397967A CN114397967A CN202210015493.0A CN202210015493A CN114397967A CN 114397967 A CN114397967 A CN 114397967A CN 202210015493 A CN202210015493 A CN 202210015493A CN 114397967 A CN114397967 A CN 114397967A
- Authority
- CN
- China
- Prior art keywords
- keywords
- database
- input
- statement
- keyword
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 16
- 238000012544 monitoring process Methods 0.000 claims description 2
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/02—Input arrangements using manually operated switches, e.g. using keyboards or dials
- G06F3/023—Arrangements for converting discrete items of information into a coded form, e.g. arrangements for interpreting keyboard generated codes as alphanumeric codes, operand codes or instruction codes
- G06F3/0233—Character input methods
- G06F3/0237—Character input methods using prediction or retrieval techniques
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Human Computer Interaction (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention provides an automatic association method for auxiliary input keywords of a database, which belongs to the technical field of distributed databases. The invention can prompt the input of associated query sentence keywords. The time for inputting the sentence is saved, and the use is easier and more convenient.
Description
Technical Field
The invention relates to the technical field of distributed databases, in particular to an automatic association method for auxiliary input keywords of a database.
Background
When the current database is queried, relevant keyword association is not carried out, a user needs to remember all query sentences, a large number of query sentences need to be manually input during query, the query is not convenient for the user to use, the query difficulty is increased, a plurality of users in non-relevant fields use difficulty to be increased, when the user remembers how to query sentences by keywords, the learning difficulty is high, and the user is not easy to input sentences quickly.
Conventional databases do not support secondary input-associative input, which is also a time-consuming operation in input.
When a database is queried, a query sentence is required to be input more quickly, and even a long keyword is forgotten to be spelled sometimes, so that the query sentence needs to be consulted, and time is wasted.
Disclosure of Invention
In order to solve the technical problems, the invention provides an automatic association method of auxiliary input keywords of a database. The associated query statement keyword input can be prompted. The time for inputting the sentence is saved, and the use is easier and more convenient.
The technical scheme of the invention is as follows:
an automatic association method of auxiliary input keywords of a database,
when the database is queried in a statement, keywords are extracted through the content input by a user, the keywords are searched and matched in the keyword database, and the keyword database is arranged in a descending order according to the keyword sequence with the largest searching times, so that the associated keywords with the highest matching degree are selected.
When a database statement is queried, a history query statement is recorded, a prompt appears once a related statement with high similarity is matched, if the statement is selected, a new statement is recorded as a new statement, and a record table exists as a temporary table. As the database is created, it is deleted by exiting the database
Further, in the above-mentioned case,
firstly, monitoring a database input frame, extracting keywords through the content input by a user, searching and matching the keywords in a keyword database, arranging the keyword database in a descending order according to the keyword sequence with the largest searching times, matching whether the current input is similar historical input sentences with a historical record database or not every time the user inputs the keywords, and matching related associated keywords with the keyword database when the historical database has similar sentences and similar keywords.
In addition, regarding the storage mode of the keyword data, the keyword data are sorted in a descending order according to the times of selecting the keywords and the times of using the keywords by the user, when the keywords are associated, the keyword data are preferably searched for and prompted by the fact that the number of times of using the keywords is large, if the keywords are selected by the user through typing, the number of times of the keywords is added by 1, and if the keywords in the input of the user are not input through association matching and typing but are manually input, the number of times of using the keywords is also added by 1.
The history data should be a temporary table, which is automatically created when the database is used to store the history, and is cleared when the database is exited. When a user inputs a statement, the statement is recorded in the history list, similar statement prompts input by the history are given by matching the history list when the user inputs the statement, and if the statement is the statement, the statement is selected. If not, the record is saved as a new added record.
The invention has the advantages that
1) The method helps users to conveniently and quickly query the database, and is quicker and more convenient than the traditional database statement input mode.
2) The user does not need to memorize the detailed sentence keyword spelling, and only needs to memorize the first few spellings of a probable keyword to be assisted by the associated vocabulary.
3) For the repeatedly input query statement, repeated manual typing is not needed, and the historical input query statement can be associated by simply using a plurality of initial keywords.
4) For the query sentence keywords that have been input, several subsequent keywords whose matching times are from high to low can be imagined and matching can be performed by selecting the keywords.
5) The query speed of the user is accelerated in a simple mode.
Drawings
Fig. 1 is a flow chart of sentence auto-association.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer and more complete, the technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention, and based on the embodiments of the present invention, all other embodiments obtained by a person of ordinary skill in the art without creative efforts belong to the scope of the present invention.
When a user inputs a database query sentence, a sentence record table and a keyword record table which are input by history are searched at the same time, if the matching probability of keywords input by the current user in the history record table is high, prompting is carried out, keyword association matching is also carried out, if the keywords are prompted, the number of times of association of related keywords is increased by 1, and if the selected history input sentence is the current sentence which is about to be input, no operation is carried out. If the user input is not historical, the statement is recorded in the historical statement after the completion of the run (whether failure or not). Also if a new key is matched, the new key will be recorded and 1 will be added to the number of matches.
The key word record table is used for storing key words and matched key words, and can be provided with a main key and a foreign key, can be associated with a plurality of matched key words, and can also take the ID of the table per se as the foreign key. And establishing a matching degree relation with the keywords of the self table. If the prompted keyword is the keyword needing to be input, the matching times are added with 1 after the user selects, and if the input keyword is not matched with the existing keyword, a new keyword matching record is added.
Storing keyword model table
| ID | Key word | Number of matches | Next matching key |
| 1 | create | 100 | table |
The history input statement recording table is mainly used for recording history statements input from the use of a database to the present, when a user uses the history statements, keyword comparison is carried out, the history statement with the highest similarity is prompted, and if the history statements are the statements, the times are added by 1 after the history statements are selected to be automatically filled. If no history statements are matched, the new statements will be recorded in the table. And the table should be a temporary table that is deleted as the database exits.
Historical record statement model table
| ID | stmt | times |
| 1 | “ALTER TABLE t ALTER PRIMARY KEY USING COLUMNS(y,z)” | 2 |
The method can prompt the next keywords through the currently input keywords, can prompt the historically input sentences, can record the new keywords, and can record the newly input database query sentences.
By searching the keyword record table, the keyword possibly matched with the keyword is found, for example, the keyword matched with the create may be table or index, etc.
The database query statements once input by the user can be recorded through the history table. If the sentence is an existing sentence, the input can be directly selected, and if the sentence is an absent sentence, the input is re-recorded.
The input speed can be accelerated through the prompting of keywords and historical sentences.
The above description is only a preferred embodiment of the present invention, and is only used to illustrate the technical solutions of the present invention, and not to limit the protection scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (8)
1. An automatic association method of auxiliary input keywords of a database is characterized in that,
when the database is queried in a statement, keywords are extracted through the content input by a user, the keywords are searched and matched in the keyword database, and the keyword database is arranged in a descending order according to the keyword sequence with the largest searching times, so that the associated keywords with the highest matching degree are selected.
2. The method of claim 1,
when a database statement is queried, the history query statement is recorded, a prompt appears once a statement with the highest relevant similarity is matched, if the statement is selected, a new statement is recorded as a new statement, and a record table exists as a temporary table.
3. The method of claim 2,
and (4) the record table is deleted after exiting the database as the database is started to be created.
4. The method of claim 3,
firstly, monitoring a database input frame, extracting keywords through the content input by a user, searching and matching the keywords in a keyword database, arranging the keyword database in a descending order according to the keyword sequence with the largest searching times, matching whether the current input is similar historical input sentences with a historical record database or not every time the user inputs the keywords, and matching related associated keywords with the keyword database when the historical database has similar sentences and similar keywords.
5. The method of claim 4,
the storage mode of the keyword data is sorted in a descending order according to the times of selecting the keywords and the times of using the keywords by the user, the keywords are preferably searched for and prompted to be used for the most times when being associated, if the keywords are selected by the user through typing, the related times are added by 1, and if the keywords in the input of the user are not input through association matching and typing but are manually input, the related times are also added by 1.
6. The method of claim 4,
the historical record data is a temporary table, a temporary table for storing the current historical record is automatically created when the database is used, and the historical record data is cleared when the database is quitted.
7. The method of claim 6,
when a user inputs a statement, the statement is recorded in the history table, similar statement prompts input by the history can be given by matching the history table when the user inputs the statement, and if the statement is selected; if not, the record is saved as a new added record.
8. The method of claim 7,
when a user inputs a database query sentence, a sentence record table and a keyword record table which are input by history are searched simultaneously, if the matching probability of keywords input by the current user in the history record table is high, prompting is carried out, and keyword association matching is also carried out simultaneously, if the keywords are prompted, the number of times of correlation of related keywords is increased by 1, and if the selected history input sentence is the current sentence which is input at present, no operation is carried out; if the user inputs the historical statement, the historical statement is recorded after the operation is completed (whether the operation is failed or not); also if a new key is matched, the new key will be recorded and 1 will be added to the number of matches.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210015493.0A CN114397967A (en) | 2022-01-07 | 2022-01-07 | Automatic association method for auxiliary input keywords of database |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210015493.0A CN114397967A (en) | 2022-01-07 | 2022-01-07 | Automatic association method for auxiliary input keywords of database |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114397967A true CN114397967A (en) | 2022-04-26 |
Family
ID=81228949
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210015493.0A Pending CN114397967A (en) | 2022-01-07 | 2022-01-07 | Automatic association method for auxiliary input keywords of database |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114397967A (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040019587A1 (en) * | 2002-07-25 | 2004-01-29 | You-Chin Fuh | Method and device for processing a query in a database management system |
| WO2008131465A1 (en) * | 2007-04-27 | 2008-11-06 | Mediareif Möstl & Reif Kommunikations- Und Informationstechnologien Oeg | Method for controlling a relational database system |
| US20160299946A1 (en) * | 2015-04-10 | 2016-10-13 | Dell Software, Inc. | Usage and Symptom Oriented SQL Statement Optimization |
| WO2017107457A1 (en) * | 2015-12-25 | 2017-06-29 | 乐视控股（北京）有限公司 | Query recommendation method and apparatus |
| CN109597824A (en) * | 2018-11-27 | 2019-04-09 | 上海炬宏信息技术有限公司 | The efficient write method of SQL statement |
| CN112035727A (en) * | 2019-06-03 | 2020-12-04 | 阿里巴巴集团控股有限公司 | Information acquisition method, device, equipment, system and readable storage medium |
-
2022
- 2022-01-07 CN CN202210015493.0A patent/CN114397967A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040019587A1 (en) * | 2002-07-25 | 2004-01-29 | You-Chin Fuh | Method and device for processing a query in a database management system |
| WO2008131465A1 (en) * | 2007-04-27 | 2008-11-06 | Mediareif Möstl & Reif Kommunikations- Und Informationstechnologien Oeg | Method for controlling a relational database system |
| US20160299946A1 (en) * | 2015-04-10 | 2016-10-13 | Dell Software, Inc. | Usage and Symptom Oriented SQL Statement Optimization |
| WO2017107457A1 (en) * | 2015-12-25 | 2017-06-29 | 乐视控股（北京）有限公司 | Query recommendation method and apparatus |
| CN109597824A (en) * | 2018-11-27 | 2019-04-09 | 上海炬宏信息技术有限公司 | The efficient write method of SQL statement |
| CN112035727A (en) * | 2019-06-03 | 2020-12-04 | 阿里巴巴集团控股有限公司 | Information acquisition method, device, equipment, system and readable storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8321442B2 (en) | Searching and matching of data | |
| US5572423A (en) | Method for correcting spelling using error frequencies | |
| US7124085B2 (en) | Constraint-based speech recognition system and method | |
| US20190278812A1 (en) | Model generation device, text search device, model generation method, text search method, data structure, and program | |
| CN110851559B (en) | Automatic data element identification method and identification system | |
| CN103365925A (en) | Method for acquiring polyphone spelling, method for retrieving based on spelling, and corresponding devices | |
| CN102365639B (en) | Retrieval device | |
| Mandal et al. | Clustering-based Bangla spell checker | |
| US8682900B2 (en) | System, method and computer program product for documents retrieval | |
| US7797152B1 (en) | Method of database searching | |
| Zahoranský et al. | Text search of surnames in some slavic and other morphologically rich languages using rule based phonetic algorithms | |
| CN113032371A (en) | Database grammar analysis method and device and computer equipment | |
| US7761286B1 (en) | Natural language database searching using morphological query term expansion | |
| CN114397967A (en) | Automatic association method for auxiliary input keywords of database | |
| CN114818663B (en) | Hierarchical intelligent pinyin and character matching method | |
| CN114861649B (en) | Pinyin and character matching method oriented to professional field | |
| van Schooten et al. | Handling speech input in the Ritel QA dialogue system | |
| CN114896382A (en) | Artificial intelligent question-answering model generation method, question-answering method, device and storage medium | |
| CN111090338B (en) | Training method of HMM (hidden Markov model) input method model of medical document, input method model and input method | |
| CN111144096A (en) | HMM-based pinyin completion training method, completion model, completion method and completion input method | |
| JP7305077B2 (en) | Information processing device, abstract output method, and abstract output program | |
| CN117112736B (en) | Information retrieval analysis method and system based on semantic analysis model | |
| Goslin et al. | English Language Spelling Correction as an Information Retrieval Task Using Wikipedia Search Statistics | |
| CN108304430B (en) | Method for modifying database | |
| JPH0612451A (en) | Illustrative sentence retrieving system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20221129 Address after: Room 305-22, Building 2, No. 1158 Zhangdong Road and No. 1059 Dangui Road, China (Shanghai) Pilot Free Trade Zone, Pudong New Area, Shanghai, 200120 Applicant after: Shanghai Yunxi Technology Co.,Ltd. Address before: Building S02, 1036 Gaoxin Langchao Road, Jinan, Shandong 250100 Applicant before: Shandong Inspur Scientific Research Institute Co.,Ltd. |