CN100530187C - Method for converting search inquiry into inquiry statement - Google Patents
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- CN100530187C CN100530187C CNB2007100008465A CN200710000846A CN100530187C CN 100530187 C CN100530187 C CN 100530187C CN B2007100008465 A CNB2007100008465 A CN B2007100008465A CN 200710000846 A CN200710000846 A CN 200710000846A CN 100530187 C CN100530187 C CN 100530187C
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Abstract
A method for storing information includes setting-up search table and semanteme matching table, setting up classification search matching table and setting up search corresponding-matching table. The method for converting search request to be query statement includes carrying out word treatment to obtain a numbers of words, converting said words to be query statement by utilizing databank semanteme matching technique and converting semanteme to be query statement by utilizing said technique and by querying match-table of statement section.
Description
Technical field
The present invention relates to the wireless search field, refer to that especially a kind of searching request is converted to the method for query statement.
Background technology
Since occurring from Web, developed into a huge globalization information resource database through short more than ten years.Quantity of information on the Web makes the user search needed information thereon and becomes difficult unusually with the speed increment of geometric series.In the case, how to retrieve Web information effectively and also just become an important research project.
The quality that improves the Web information retrieval comprises two aspect contents: be how to design the better retrieval technology on existing resources on the one hand, be how to be the understandable content of resource affix computing machine on the Web on the other hand, be convenient to computing machine and handle better, just provide the means of the accessible expression resource of a kind of computing machine.At latter event, Berners-Lee has proposed Semantic Web.The target of Semantic Web is to make the information on the Web have the understandable semanteme of computing machine, satisfies intelligence software and acts on behalf of Agent goes up isomery and distributed intelligence to WWW effective visit and search.In the architecture of Semantic Web, Ontology has the status of core, can solve the insoluble problem of classic method, has multiple lexical representation and same speech to have multiple implication the same as same notion.The accurate implication of Ontology by the strict difinition and the relation between notion and the notion of notion are determined notion, expression is common approval, sharable knowledge, becomes in the Semantic Web basis of information sharing and exchange on the semantic hierarchies.
Semantic Web is an emerging research direction, also just begins as the Ontology of Semantic Web core status, wherein has problems to study and to solve.For example, how information is stored and could make the search precision height, and the problem that how searching request is converted to query statement, still be in theoretical research stage so far, do not find the proven technique scheme.
Summary of the invention
The problem to be solved in the present invention provides a kind of method that can make the high searching request of search precision be converted to query statement.
In order to address the above problem, the technical scheme that searching request of the present invention is converted to the method for query statement comprises step:
Set up search list, a search list is deposited pairing all search datas of search main body;
Set up the semantic matches table, a semantic matches table is deposited the pairing query statement fragment of all conditions class word of describing a search main body;
Set up the classification search matching list, classification search matching list is deposited all search principal names of belonging to a classification and each search pairing search list title of main body and semantic matches table name and is claimed;
Set up the corresponding matching list of search, a corresponding matching list of search is deposited the item name and the pairing classification search matching list of each item name of all search main bodys.
Set up the word sorted table, word sorted table deposits word and affiliated item name and this class name claims whether be the search main body.
Searching request is carried out word segmentation processing obtain plurality of words, described participle refers to continuous word sequence is reassembled into the process of word sequence according to certain matched rule, and described word refers to Chinese vocabulary;
Utilize database semantic matches technology that described plurality of words is converted to query statement, described database semantic matches technology refers to the matching list by the semanteme of word and query statement fragment, is the technology of query statement with semantic conversion.
Further, described step is utilized database technology that described plurality of words is converted to query statement further to comprise:
Determine the classification of the word that the process word segmentation processing obtains and determine the search main body according to described token-category, described search main body refers to the object search of searching request statement;
Determine the search matched table according to the token-category of described search main body, described classification search matching list is the corresponding relation that is used to describe between search main body and search list, the semantic matches table;
Determine pairing search list of searching request and semantic matches table according to described classification search matching list, described search list refers to comprise the table of search data, and it is corresponding one by one with the search main body, described semantic matches table refers to that word types is the semanteme of word of condition class and the corresponding tables of database SQL query statement fragment, and the corresponding semantic matches table of each search list;
Generate query statement according to the semantic matches table.
Further, described step further comprises according to semantic matches table generation query statement:
The main part of query statement is defined as: Select search main body From search list;
From the semantic matches table, find out with searching request in the corresponding part of condition class word and with these parts with and relation connect into the condition part of query statement.
Compared with prior art, searching request of the present invention is converted to the method beneficial effect of query statement and is:
At first, owing to set up the corresponding relation of search main body all search datas pairing and semantic matches table, make it possible to searching request and correspond to query statement fast, the search precision height with it.
Secondly,, utilize database semantic matches technology that plurality of words is converted to query statement again, therefore make search very accurate owing to earlier searching request has been cut into plurality of words.
Description of drawings
Fig. 1 is the process flow diagram that searching request of the present invention is converted to the method for query statement;
Fig. 2 is the step 2 among Fig. 1) the process flow diagram of further decomposition;
Fig. 3 is the step 24 among Fig. 2) the process flow diagram of further decomposition;
Fig. 4 is the process flow diagram of the information storage means among the present invention.
Embodiment
As shown in Figure 4, information storage means used in the present invention comprise the steps:
A1) set up search list, a search list is deposited pairing all search datas of search main body;
A2) set up the semantic matches table, a semantic matches table is deposited the pairing query statement fragment of all conditions class word of describing a search main body;
A3) set up the classification search matching list, classification search matching list is deposited all search principal names of belonging to a classification and each search pairing search list title of main body and semantic matches table name and is claimed;
A4) set up the corresponding matching list of search, a corresponding matching list of search is deposited the item name and the pairing classification search matching list of each item name of all search main bodys.
Further, the information storage means among the present invention also comprise step a5) set up the word sorted table, word sorted table deposits word and affiliated item name and this class name claims whether be the search main body.
Further, the information storage means among the present invention also comprise step a6) to set up and divide dictionary, it comprises some minutes vocabularys, each divides vocabulary to be used to deposit word name and word occurrence rate.
From the above, information storage means among the present invention are to be unit with the search main body, for each search main body pairing all data is set up a search list, that is to say, will all leave in the search list with corresponding all data of search main body.Described search main body refers to the object search of searching request statement.For example colour TV this search main body, with pairing all deposit data of colour TV in search list T1, suppose that pairing all data of colour TV include only these five types of colour TV ID, colour TV title, Display Category, size and prices, as follows at search list T1 so:
| Colour TV ID | The colour TV title | Display Category | Size | Price |
| 000001 | TCL-129888 | Liquid crystal | 42 | 9800 |
| ...... | ...... | ...... | ...... | ...... |
Table T1
In this table, deposit the information such as title, Display Category, size and price of all colour TVs.
Information storage means among the present invention also will be used for describing each pairing query statement fragment of all conditions class word of searching for main body and leave the semantic matches table in.Described condition class word refers to be used for the word of limit search main body, for example 42 cun, the most cheap and the most expensive or the like.
Usually, the semantic matches table comprises two fields at least, and a field is the semantic description field, is used to deposit the condition class word of describing the search main body; A field is the SQL fragment, is used to deposit the pairing query statement fragment of each condition class word.
For example following table T1_L1 is to deposit all conditions class word and the pairing query statement fragment thereof of describing search main body colour TV.
| Semantic description | The SQL fragment |
| Class name | Display Category field=class name |
| % cun (% represents digital parameters) | Size field=% |
| The most expensive | Price field name=(select Max (price field name) from t1 WHERE class conddition AND size condition) |
| The most cheap | Price field name=(select Max (price field name) from t1 WHERE class conddition AND size condition) |
| Price at a between the b | A＜=price field name＜=b |
| ...... | ...... |
After search list and semantic matches table are all set up, set up the one-to-one relationship of search main body and search list and semantic matches table, can set up the classification search matching list, each classification search matching list is deposited and is belonged to such other all search principal names and the search pairing search list title of main body and semantic matches table name and claim; Example is as shown in table 1 below, is the classification search matching list of a commodity class:
| Trade name | Search list | The semantic matches table |
| Colour TV | T1 | T1_L1 |
| ...... | ...... | ...... |
Table 1
Wherein: search main body colour TV, its search list is T1, its semantic matches table is T1_L1.
Because corresponding classification search matching list of classification, below just need to set up the classification under the search main body and the one-to-one relationship of classification search matching list, can realize by setting up the corresponding matching list of search, search for corresponding matching list and comprise two fields at least, a field is for searching for the item name of main body, and another field is the pairing classification search matching list of item name.Example is as shown in table 2 below:
| Belong to the token-category of searching for main body | The search matched table |
| Merchandise classification | Merchandise classification search matched table |
| The place name classification | Place name classification search matching list |
| ...... | ...... |
Table 2
Further, the information storage means among the present invention also comprise step a5) set up the word sorted table, word sorted table deposits word and affiliated item name and this class name claims whether be the search main body.As shown in table 3:
| Word | Classification |
| Colour TV | Merchandise classification |
| The most cheap | The condition classification |
| ...... | ...... |
Table 3
Further, the information storage means among the present invention also comprise step a6) to set up and divide dictionary, it comprises some minutes vocabularys, each divides vocabulary to be used to deposit word name and word occurrence rate.Dividing dictionary is a very proven technique.
Therefore, in the information storage means in the present invention, set up the corresponding relation of search main body and pairing search list and semantic matches table, so the information storage means among the present invention, can fast search be asked clearly with query statement to interrelate, improve retrieval rate and precision.
Correspondingly, as shown in Figure 1, the method that searching request of the present invention is converted to query statement also comprises step:
1) searching request is carried out word segmentation processing and obtain plurality of words, described participle refers to continuous word sequence is reassembled into the process of word sequence according to certain matched rule, and described word refers to Chinese vocabulary;
2) utilize database semantic matches technology that described plurality of words is converted to query statement, described database semantic matches technology refers to the matching list by the semanteme of word and query statement fragment, is the technology of query statement with semantic conversion.
Wherein, as shown in Figure 2, step 2) further comprise:
21) determine the classification of the word that obtains through word segmentation processing and determine the search main body according to described token-category, described search main body refers to the object search of searching request statement;
22) determine the classification search matching list according to the token-category of described search main body, described classification search matching list is the corresponding relation that is used to describe between search main body and search list, the semantic matches table;
23) determine pairing search list of searching request and semantic matches table according to described classification search matching list, described search list refers to comprise the table of search data, and it is corresponding one by one with the search main body, described semantic matches table refers to that word types is the semanteme of word of condition class and the corresponding tables of database SQL query statement fragment, and the corresponding semantic matches table of each search list;
24) generate query statement according to the semantic matches table.
As shown in Figure 3, step 24) further comprise:
241) main part with query statement is defined as: Select search main body From search list;
242) from the semantic matches table, find out with searching request in the corresponding part of condition class word and with these parts with and relation connect into the condition part of query statement.
From the above, the technical scheme that searching request of the present invention is converted to the method for query statement is earlier searching request to be carried out word segmentation processing to obtain plurality of words, can adopt the word matched method, the word of just searching in the searching request in minute dictionary to be comprised.Dictionary was often referred to Chinese lexical data base in described minute, divided dictionary to comprise some minutes vocabularys, and each divides vocabulary to comprise two fields at least: word name and word occurrence rate (probability of representing this word to occur).Dividing dictionary now has been very ripe database, can buy from various research institutions such as (as Tsing-Hua University) of university.For example searching request is: 42 cun the most cheap lcd-tvs, from minute dictionary, can find " the most cheap ", " ", " 42 cun ", " liquid crystal " and " colour TV " totally 5 words, therefore through step 1) can be with this searching request cutting " the most cheap ", " ", " 42 cun ", " liquid crystal " and " colour TV " these five words.
After the searching request cutting is word, determine the classification of each word, described classification refers to be used to describe the search field under the word, and each search field is called a classification.Can determine the classification of word according to minute word class table.Described minute word class table refers to deposit the table of word and affiliated classification thereof, mainly comprises two fields, and a field is a word, and a field is a classification.As shown in table 3.
Wherein, the classification of word " colour TV " is " merchandise classification "; The classification of word " the most cheap " is " condition classification " or the like.Classification can comprise merchandise classification, condition classification, modify classification, price classification, digital classification, place name classification or the like.
Determine the search main body of searching request, can obtain by classification and search main body matching list.Described classification and search main body matching list refer to be used to show whether each classification is the search main body, and this table one is thrown and comprised two fields, and a field is a classification, and whether field is for searching for main body, as shown in table 4:
| Classification | Whether search for main body |
| Merchandise classification | Be |
| The condition classification | Not |
| ...... | ...... |
Table 4
Wherein, classification " merchandise classification " is the search main body, and classification " condition classification " is not the search main body." colour TV " is the search main body of searching request " 42 cun the most cheap lcd-tvs ".
Below, determine the search matched table according to the search main body, can realize that generally the corresponding matching list of described search is used to show and belongs to the pairing search matched table of the token-category of searching for main body by searching for corresponding matching list.Generally, search for corresponding matching list and comprise two fields, a field is " belonging to the token-category of searching for main body ", a field is " a search matched table ", as shown in table 2, wherein, belong to the pairing search matched table of token-category " merchandise classification " of searching for main body and be " merchandise classification search matched table "; Belong to the pairing search matched table of token-category " place name classification " of searching for main body and be " place name classification search matching list "; Or the like.
From this table as can be known, the search matched table of the search main body " TV " of searching request " 42 cun the most cheap LCD TV " is " a merchandise classification search matched table ".
After having obtained the search matched table, just can know pairing search list of searching request and semantic matches table by the search matched table.Usually, the search matched table comprises three fields at least: search principal name, search list title, semantic matches table name claim.Each the corresponding search list of search main body and a semantic matches table.As shown in table 1, be a merchandise classification search matched table, wherein, the pairing search list of trade name " colour TV " is " T1 ", pairing semantic matches table is " T1_L1 ".Table T1 is used to deposit the information of various model colour TVs, mainly comprises " Display Category ", " size ", " price " or the like.Table T1_L1 is the pairing semantic matches table of search list T1 T1_L1, and wherein, the semantic description field is represented the condition class semanteme of word, and the SQL fragment field is represented the SQL fragment of condition class word correspondence.
Because the search main body of searching request " 42 cun the most cheap lcd-tvs " is " colour TV ", search list is " T1 ", and therefore, the main part that can draw query statement is:
Select colour TV title From T1
Other words: " the most cheap ", " ", " 42 cun " and " liquid crystal ", wherein " " belong to the modification classification, do not influence semanteme, can neglect." the most cheap ", " 42 cun " and " liquid crystal " belong to the condition classification, and the SQL fragment that therefore inquires correspondence respectively in the semantic matches table is as follows:
For " liquid crystal ": the Display Category field=' liquid crystal '
Wherein: the method that judgement " liquid crystal " belongs to class name is:
Can use following SQL statement to " the most cheap ", " 42 cun " and " liquid crystal ":
SELECT Display Category FROM T1 WHERE Display Category=condition class word
If above SQL statement return results equals 1, just illustrate that this condition class word is a Display Category.
For " 42 cun ": big or small condition field=42
Wherein: judge that 42 cun is M cun method, can use following SQL statement to " the most cheap ", " 42 cun " and " liquid crystal ":
SELECT*FROM T1_L1 Where semantic description like condition class word
If above SQL statement return results equals 1, just illustrate that this condition class word is % cun, replace % with 42 then, can obtain %=42.
For " the most cheap ": price field name=(select Max (price field name) from t1 WHERE Display Category field=' liquid crystal ' AND size condition field=42)
Wherein: the SQL fragment that " the most cheap " is corresponding is: price field name=(select Max (price field name) from t1 WHERE class conddition AND size condition, class conddition and two SQL fragments above the big or small condition correspondence are replaced with above two SQL fragments and to be got final product.
Obtained the SQL fragment of three condition class word correspondences in this searching request by above-mentioned steps, three conditions splicings can have been obtained the condition part of SQL statement:
WHERE Display Category field=' liquid crystal ' AND size condition field=42 AND (selectMax (price field name) from t1 WHERE Display Category field=' liquid crystal ' AND size condition field=42)
Main part and condition part splicing with query statement at last can obtain complete SQL statement:
SELECT colour TV title FROM T1 WHERE price field name=(select Max (price field name) from t1 WHERE Display Category field=' liquid crystal ' AND size condition field=42) AND Display Category field=' liquid crystal ' AND size condition field=42
In sum, adopt searching request of the present invention to be converted to the technical scheme of the method for query statement, can make that search is very accurate.
Claims (6)
1, a kind of searching request is converted to the method for query statement, it is characterized in that, comprising:
Set up search list, a search list is deposited pairing all search datas of search main body;
Set up the semantic matches table, a semantic matches table is deposited the pairing query statement fragment of all conditions class word of describing a search main body;
Set up the classification search matching list, classification search matching list is deposited all search principal names of belonging to a classification and each search pairing search list title of main body and semantic matches table name and is claimed;
Set up the corresponding matching list of search, a corresponding matching list of search is deposited the item name and the pairing classification search matching list of each item name of all search main bodys;
Set up the word sorted table, word sorted table deposits word and affiliated item name and this class name claims whether be the search main body;
Searching request is carried out word segmentation processing obtain plurality of words, described participle refers to continuous word sequence is reassembled into the process of word sequence according to certain matched rule, and described word refers to Chinese vocabulary;
Utilize database semantic matches technology that described plurality of words is converted to query statement, described database semantic matches technology refers to the matching list by the semanteme of word and query statement fragment, is the technology of query statement with semantic conversion.
2, searching request as claimed in claim 1 is converted to the method for query statement, it is characterized in that, described step is utilized database semantic matches technology that described plurality of words is converted to query statement further to comprise:
Determine the classification of the word that the process word segmentation processing obtains and determine the search main body according to described token-category, described search main body refers to the object search of searching request statement;
Determine the classification search matching list according to the token-category of described search main body, described classification search matching list is the corresponding relation that is used to describe between search main body and search list, the semantic matches table;
Determine pairing search list of searching request and semantic matches table according to described classification search matching list, described search list refers to comprise the table of search data, and it is corresponding one by one with the search main body, described semantic matches table refers to that word types is the semanteme of word of condition class and the corresponding tables of database SQL query statement fragment, and the corresponding semantic matches table of each search list;
Generate query statement according to the semantic matches table.
3, searching request as claimed in claim 2 is converted to the method for query statement, it is characterized in that, described step generates query statement according to the semantic matches table and further comprises:
The main part of query statement is defined as: Select search main body From search list;
From the semantic matches table, find out with searching request in the corresponding part of condition class word and with these parts with and relation connect into the condition part of query statement.
4, searching request as claimed in claim 1 is converted to the method for query statement, it is characterized in that, sets up after setting up the word sorted table and divides dictionary, and it comprises some minutes vocabularys, and each divides vocabulary to be used to deposit word name and word occurrence rate.
5, searching request as claimed in claim 4 is converted to the method for query statement, it is characterized in that, described step is utilized database semantic matches technology that described plurality of words is converted to query statement further to comprise:
Determine the classification of the word that the process word segmentation processing obtains and determine the search main body according to described token-category, described search main body refers to the object search of searching request statement;
Determine the classification search matching list according to the token-category of described search main body, described classification search matching list is the corresponding relation that is used to describe between search main body and search list, the semantic matches table;
Determine pairing search list of searching request and semantic matches table according to described classification search matching list, described search list refers to comprise the table of search data, and it is corresponding one by one with the search main body, described semantic matches table refers to that word types is the semanteme of word of condition class and the corresponding tables of database SQL query statement fragment, and the corresponding semantic matches table of each search list;
Generate query statement according to the semantic matches table.
6, searching request as claimed in claim 5 is converted to the method for query statement, it is characterized in that, described step generates query statement according to the semantic matches table and further comprises:
The main part of query statement is defined as: Select search main body From search list;
From the semantic matches table, find out with searching request in the corresponding part of condition class word and with these parts with and relation connect into the condition part of query statement.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101876981B (en) * | 2009-04-29 | 2015-09-23 | 阿里巴巴集团控股有限公司 | A kind of method and device building knowledge base |
| CN102073725B (en) * | 2011-01-11 | 2013-05-08 | 百度在线网络技术（北京）有限公司 | Method for searching structured data and search engine system for implementing same |
| CN102073726B (en) * | 2011-01-11 | 2014-08-06 | 百度在线网络技术（北京）有限公司 | Structured data import method and device for search engine system |
| CN103020083B (en) * | 2011-09-23 | 2016-06-15 | 北京百度网讯科技有限公司 | The automatic mining method of demand recognition template, demand recognition methods and corresponding device |
| CN103455491B (en) * | 2012-05-29 | 2018-02-06 | 深圳市世纪光速信息技术有限公司 | To the method and device of query word classification |
| CN103455638A (en) * | 2013-09-26 | 2013-12-18 | 中国科学院自动化研究所 | Behavior knowledge extracting method and device combining reasoning and semi-automatic learning |
| CN104615645A (en) * | 2014-12-18 | 2015-05-13 | 百度在线网络技术（北京）有限公司 | Search implementation method, device and system and computer equipment |
| CN105786928A (en) * | 2014-12-26 | 2016-07-20 | 北大医疗信息技术有限公司 | Medical system data query method and medical system data query system |
| CN106033466A (en) * | 2015-03-20 | 2016-10-19 | 华为技术有限公司 | Database query method and device |
| CN106775770B (en) * | 2017-01-16 | 2020-08-11 | 兴唐通信科技有限公司 | Search method for constructing query statement based on class information |
| CN109993592A (en) * | 2017-12-29 | 2019-07-09 | 北京京东尚科信息技术有限公司 | Information-pushing method and device |
| CN109977277A (en) * | 2019-04-04 | 2019-07-05 | 明觉科技（北京）有限公司 | Automobile information querying method, device and electronic equipment based on searching system |
| CN110399432A (en) * | 2019-07-23 | 2019-11-01 | 杭州城市大数据运营有限公司 | A kind of classification method of table, device, computer equipment and storage medium |
| CN110489603A (en) * | 2019-07-30 | 2019-11-22 | 东软集团股份有限公司 | A kind of method for information retrieval, device and vehicle device |
| CN111259037B (en) * | 2020-01-14 | 2023-09-19 | 重庆特斯联智慧科技股份有限公司 | Data query method and device based on rule configuration, storage medium and terminal |
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