CN104866593B - A kind of database search method of knowledge based collection of illustrative plates - Google Patents
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Abstract
The present invention relates to a kind of database search methods of knowledge based collection of illustrative plates, belong to structural data excavation and search field.Method proposed by the present invention first analyzes the elements such as constraint between database table type and table, then generates relation between corresponding concept, entity and entity using constraint between table and table, and establishes knowledge mapping service accordingly.After natural language querying input by user is obtained, the feature schema inquired about and element value are detected to each element of user's inquiry, then feature schema is matched to obtain corresponding query pattern in template library, then the element value of inquiry is filled into query pattern to obtain knowledge mapping query statement, the query statement is finally performed in knowledge mapping service, the corresponding knowledge of user's inquiry is obtained and returns to user.Data and internal relation in database can effectively be organized and showed to method proposed by the present invention, and support the natural language querying of user, so as to improve the user experience of database search.
Description
Technical field
The present invention relates to structural data excavation and searching method, more particularly to a kind of support users of knowledge based collection of illustrative plates
The database search method of natural language querying.
Background technology
Knowledge mapping technology (Knowledge Graph) is to develop most noticeable skill in knowledge engineering field at present
Art.Knowledge mapping is exactly that the relation between knowledge and knowledge is indicated with figure (Graph) model in simple terms, the node of figure
The concept or entity involved by knowledge are represented, the side of figure represents the relation between concept or entity, what numerous nodes and side were formed
Figure can carry out knowledge complete and clearly describe.A large amount of knowledge mappings are integrated and according to knowledge hierarchy taxonomic organizations,
It is formed knowledge base (Knowledge Base).In recent years, built by internet crowdsourcing mode or algorithm extract automatically,
Some knowledge bases for including magnanimity entity are formd, more well-known knowledge base has YAGO, DBpedia, Freebase etc..At present
Knowledge mapping technical support many revolutionary services and application.Such as Google, must answer, the mainstreams search engine such as Baidu exists
Result of page searching adds and the knowledge such as the relevant entity of query word；The smart mobile phones such as the Siri of apple, the Cortana of Microsoft
Assistant can answer the enquirement of user；Knowledge search engine Walfram Alpha can directly give according to problem input by user and answer
Case rather than provide relevant documentation as traditional search engine.
Although knowledge mapping technology is widely applied in the open data such as internet arena, in relation data
The traditional fields such as storehouse but rarely have application.Relational database in a structured manner stores data, supports the query statements such as SQL
Data are inquired about, are a kind of storage modes functions reliably and efficiently.But semanteme and inherent pass of the relational database to data
The tissue of system and performance Shortcomings, and the SQL query mode that relational database is provided requires user to have professional knowledge
And experience is bad.
The content of the invention
Goal of the invention：The present invention proposes a kind of branch of knowledge based collection of illustrative plates for deficiency existing for current database search
The database search method of user's natural language querying is held, to reduce database search using difficulty, improves user experience.
Technical solution：In order to solve the above-mentioned technical problem, the invention discloses a kind of databases of knowledge based collection of illustrative plates to search
Suo Fangfa handles two big steps including knowledge mapping structure and natural language querying；
The knowledge mapping structure, including：
A. factor analysis is carried out to database, and table is divided into relation between the tables of data and storage object that store specific object
Relation table, the element includes restriction relation between table name, row name and table；
B. the record in tables of data and tables of data establishes concept node and entity node；
C. according to the relation table of relation is established between entity node between foreign key constraint relation and storage object between tables of data
Relation；
D. the relation between the node that is generated in the node and step c that are generated in step b is carried out using knowledge mapping instrument
Storage, establishes knowledge mapping service；
The natural language querying processing, including：
E. query statement input by user is segmented, and the vocabulary after participle is subjected to query elements mapping, obtained
The feature schema of inquiry and element value, the query elements include variable, relation, entity and concept；
F. feature schema is matched to obtain corresponding query pattern in template library；
G. element value is filled into query pattern and obtains knowledge mapping query statement；
H. knowledge mapping query statement is performed in knowledge mapping service and obtains the corresponding knowledge of user's inquiry.
Further, the record in the step b in tables of data and tables of data establishes concept node and entity node
Method be：To each tables of data T in databaseA, a concept node C is established with table name AA；Then for table TAIn
Each records TAi, establish an entity EAi, and using each row name of this record and corresponding train value as the entity attributes and
Property value, then by concept node CAIt is directed toward entity node EAi, i is the sequence number of record.
Further, according to the method that foreign key constraint relation establishes relation between entity node between tables of data in the step c
For：If table TAIn row B be table TCThe external key of middle row D, then according to row B and the value correspondence of row D, establish table TAIn it is every
Row record TAiConstructed entity EAi, to table TCMiddle record TCjConstructed entity ECjBetween relation, the title of relation according to
Conceptual relation between table name A and C determines.
Further, the method for establishing relation between entity node in the step c according to relation table is：If relation table TCIt deposits
Tables of data T is stored upATo TBMany-one relationship, then according to table TCThe Table A major key of record to table B major keys mapping relations, to establish
Table TAThe entity E of structureAiTo table TBThe entity E of structureBjBetween relation, the title of relation determines according to table name C.
Further, query statement input by user is segmented in step e, and the vocabulary after participle is inquired about
Element maps, and the feature schema and the method for element value inquired about include：
Using natural language processing segmentation methods to inquiry O={ o input by user1o2...on, o1o2...onFor individual character,
It is segmented to obtain word segmentation result W={ w1=o1o2...ok,w2=ok+1...,...,wN=om...on, segment the dictionary used
Including the relevant vocabulary of concept, entity, attribute and relation generated in general dictionary and step c；
Defined variable (Variable, V), relation (Relation, R), entity (Entity, E), concept (Concept, C)
Four class query elements a, element each vocabulary in word segmentation result being mapped in the four classes query elements, are denoted as：＜
P, W ＞={ ＜ p1,w1＞, ＜ p2,w2＞ ... ＜ pN,wN＞ }, the element identification of each vocabulary mapping in word segmentation result is extracted
Come obtain inquiry O feature schema, be denoted as：P={ p1,p2...pN},pi∈{V,R,E,C}。
Further, the query pattern in the step f is denoted as X=f (V, R, E, C), and f (V, R, E, C) is four class elements
Generalized function, be knowledge mapping inquiry primitive and four class elements combination.
The beneficial effects of the present invention are two aspects：First, using knowledge mapping to the data in relational database into
Row tissue, can preferably mining data semanteme and inner link；Second, by being automatically analyzed to natural language querying
And conversion, can relevant knowledge directly be returned to according to natural language querying input by user, difficulty is used so as to reduce search
And improve user experience.
Description of the drawings
The present invention is done in the following with reference to the drawings and specific embodiments and is further illustrated, it is of the invention above-mentioned and/
Or otherwise advantage will become apparent.
Fig. 1 is the overview flow chart of the embodiment of the present invention；
Fig. 2 is the flow chart that the embodiment of the present invention is applied to movie database；
Fig. 3 is the knowledge mapping structure diagram based on movie database structure in the embodiment of the present invention.
Specific embodiment
As shown in Figure 1, a kind of database search method of knowledge based collection of illustrative plates disclosed by the embodiments of the present invention includes knowledge
Map construction and natural language querying handle two big steps, and wherein knowledge mapping structure is mainly analyzed including database elements, is general
The step of relation generation and knowledge mapping service are built between entity generation, entity is read, natural language querying processing mainly includes
The step of element detection, template matches, query generation and query execution.In order to become apparent from getting information about present disclosure,
The specific steps of the method for the present invention using movie database as example, will be elaborated below.Fig. 2 illustrates embodiment of the present invention side
Method applies the flow chart in movie database.Table 1 lists the table name of movie database used in example, row name and constraint etc.
Element information.
1 movie database element of table
Before each step is described in detail, technical solution of the present invention part and the letter character occurred below are explained first
It is as follows：Tee is the initial of table Table, represents the table in database, and the subscript of T represents table name.Letter C is concept
The initial of Concept, represents concept node.Letter e is the initial of entity Entity, represents entity node.TAiRepresent number
According to i-th record in table, to refer to, represent all to make similary operation to every a line record of tables of data.Arrow generation in formula
Points relationship between table node, the title of the textual representation relation above arrow.
The knowledge mapping structure in 2 pairs of the present embodiment methods and natural language querying processing procedure are made detailed below in conjunction with the accompanying drawings
It describes in detail bright.Knowledge mapping structure comprises the following steps：
Step 1. database elements are analyzed.It extracts and relevant factor in analytical database, including each table and table name, in table
The row name respectively arranged, the restriction relation between table, and further table is divided between the tables of data and storage object that store specific object
The relation table of relation.Such as：By analyzing the database shown in table 1, tables of data is obtained：Film, performer, director, film
Type, relation table：Restriction relation between film performer's table, movie director's table and tables of data.
Step 2. utilizes tables of data structure concept and entity node.To each tables of data T in databaseA, with table name A
Establish a concept node CA, sequentially for table TAIn each record TAi, establish an entity EAi, and by concept node CA
It is directed toward entity node EAi.I.e.
For each TAi∈TA
Entity EAiComprising attribute be table TAEach row name of definition, property value TAiThe value of each row.
Such as：With cast TPerformerExemplified by, initially set up a concept node CPerformer, recorded for each in cast
TPerformer i, establish an entity node EPerformer i, and by concept node CPerformerIt is directed toward entity node EPerformer i, relationships between nodes are " comprising ".
Same method is also all used to other tables of data.Fig. 3 illustrates the concept node built and part entity node.In order to reach
To effect is clearly indicated, the inclusion relation of concept node to entity node is represented using dotted arrow, relation name "comprising"
It omits without drawing.Each entity node only depicts title, and number omit without drawing.
Step 3. utilizes the relation between constraint between table or relation table structure entity node.Assuming that defined in database as
Under foreign key constraint relation：Table TAIn row B be table TCThe external key of middle row D, is denoted as
TA(B)=Foreign (TC(D))
Then according to row B and the value correspondence of row D, table T is establishedAIn often row record TAiConstructed entity EAi, arrive
Table TCMiddle record TCjConstructed entity ECjBetween relation.The title of relation is come true according to the conceptual relation between table name A and C
It is fixed, it is denoted as R (A, C).I.e.
Work as TAi(B)=TCj(D)
In above description, TAi(B) table T is representedAIn the i-th row record row B value, TCj(D) table T is representedCMiddle jth row
The value of the row D of record.
When there are during correspondence for a plurality of record of a record of some table and another table in database, it will usually make
This one-to-many relation is stored with an individual table.Due to one-to-many and many-to-one relation be it is symmetrical,
So only explanation builds entity relationship using many-one relationship table below.If table TCStore table TATo TBMany-one relationship, then
It can be according to table TCThe Table A major key of record to table B major keys mapping relations, to establish table TAThe entity E of structureAiTo table TBStructure
Entity EBjBetween relation.The title of relation is determined according to table name C, is denoted as R (C).I.e.
As R (TAi(pk), TBj(pk))∈TC
In example, film table and film types table are there are foreign key constraint relation, then for movie property node, such as fruit
Body node EFilm j" film types number " attribute be equal to film types node EFilm types k" film types number " attribute, then build
Vertical EFilm jIt is directed toward EFilm types kRelation, relation name be " type ".It can for relation table " film performer's table " and " movie director's table "
To establish actor node to the relation of film node and direct node to the relation of film node.By taking film performer's table as an example,
If certain a line T in tableFilm performer lFilm number attribute be equal to film node EFilm mFilm number attribute, performer number belong to
Property be equal to actor node EPerformer nPerformer's number attribute, then establish node EPerformer nIt is directed toward EFilm mRelation, relation name is " goes out
It drills ".Director's node is similarly established to the relation of film node, relation name is " directing ".So far, knowing based on movie database
Knowledge collection of illustrative plates, which is just built, to be completed, and Fig. 3 illustrates a sample of knowledge mapping.
Step 4. knowledge mapping service is built.Step 3 is built using the knowledge mapping instrument Cayley that increases income of Google
The knowledge mapping of completion is stored.Cayley provides Gremlin grammatical query services, and Gremlin is a kind of mapping traversal
Language, can according to while points relationship and while title carry out the inquiry of node.Table 2 illustrates some and is based on film
The query statement of database application and query result example, ' V ' in query statement represent the inquiry of node (Vertex),
Side is pointed out in ' Out ' representative, and ' In ' representative refers into side.
2 Gremlin of table inquires about example
Natural language querying processing comprises the following steps：
Step 5. dictionary is built.Vocabulary involved by entity and entity relationship is added in the dictionary of participle software.This example
Vocabulary involved by middle entity includes title, actor name, director names, the film types title of film.Involved by relation
Vocabulary has " comprising ", " directing ", the relation names such as " performance " and with these vocabulary vocabulary equivalent in meaning and similar.It can be with
Understand, the structure of dictionary can independently be built and safeguarded based on substantial amounts of priori, herein add relative words
Enter dictionary, dictionary can be expanded, improve word segmentation processing effect.
Step 6. element detects.The inquiry of user's input side is denoted as O={ o1o2...on, o1o2...onFor individual character, utilize
Chinese word segmentation instrument (such as ICTCLAS etc.) segments natural language querying input by user, and word segmentation result is W={ w1
=o1o2...ok,w2=ok+1...,...,wN=om...on}.By defining four class elements：Variable (Variable, V), relation
Vocabulary in word segmentation result can be mapped to above-mentioned by (Relation, R), entity (Entity, E), concept (Concept, C)
Each element, is denoted as：＜ P, W ＞={ ＜ p1,w1＞, ＜ p2,w2＞ ... ＜ pN,wN＞ }, wherein each two tuple, which illustrates, wants
Element and corresponding element value.Such as two tuple ＜ p1,w1W in ＞1=o1...okA vocabulary, at the same be also element value, p1It is then
The element identification of the vocabulary.The element identification of each vocabulary mapping in word segmentation result is extracted and can be obtained by wanting for inquiry O
Plain pattern, is denoted as：P={ p1,p2...pN},pi∈ { V, R, E, C }, the value range of element identification in formula：{ V, R, E, C } is
The initial of aforementioned four classes element English.
Such as the inquiry of user is O={ which actor features Around the World in 80 Days }, word segmentation result is W={ w1=which
A bit, w2=performer, w3=perform, w4=global the earth 80 days }.Word segmentation result is mapped to variable (Variable, V), relation
(Relation, R), entity (Entity, E), four class element of concept (Concept, C), can obtain element and element value corresponds to
Relation ＜ P, W ＞={ ＜ V, w1＞, ＜ C, w2＞, ＜ R, w3＞, ＜ E, w4＞ }, then the feature schema for inquiring about O is P=VCRE.
Step 7. template library is built.Feature schema is established to the mapping template of Gremlin query patterns according to syntax rule
Storehouse, each template in template library is mapping ruler of the feature schema to query pattern.Query pattern is that Gremlin is looked into
The combination of primitive and four class query elements is ask, the generalized function of four class elements is considered as, is denoted as f (V, R, E, C).Table 3 provides
One feature schema is to query pattern mapping template storehouse example.
3 feature schema of table is to query pattern mapping template storehouse example
| Feature schema | Query pattern |
| C V | g.V(C).Out() |
| V C | g.V(C).Out() |
| E R V | g.V(E).Out(R) |
| E R V C | g.V(E).Out(R).And(g.V(C).Out()) |
| V C R E | g.V(E).In(R).And(g.V(C).Out()) |
| … | … |
Step 8. template matches.It is matched in the template library that the feature schema obtained in step 6 is built in step 7,
Obtain corresponding query pattern.Such as the feature schema P=V C R E for generating query by example in step 6 are matched, it can be with
Query pattern is obtained as g.V (E) .In (R) .And (g.V (C) .Out ()).
Step 9. query generation.According to the correspondence of element in step 6 and element value, element value is inserted into step 8 and is obtained
The query pattern X=f (V, R, E, C) arrived, it is possible to generate corresponding knowledge mapping query statement, Y=f (V, R, E, C, ＜ P, W
＞)=f (w1,w2,...,wN).Such as element in step 6 example and element value correspondence are ＜ P, W ＞={ ＜ V, w1
＞, ＜ C, w2＞, ＜ R, w3＞, ＜ E, w4＞ }, by vocabulary w1,w2,w3,w4The query pattern obtained in step 8 is inserted, obtains Q
=f (V, R, E, C, ＜ P, W ＞)=g.V (w4).In(w3).And(g.V(w2) .Out ())=g.V (' the global earth 80 days ')
.In (' performing ') .And (g.V (' performer ') .Out ()).
Step 10. query execution.The query statement generated in step 9 is taken in the Cayley knowledge mappings that step 4 is built
It is performed in business, obtains query result.Such as the query execution of the example in step 9 is that result is：" Cheng Long, big vast treasure ... ".
It is pointed out that in above-mentioned steps step 5 dictionary structure and step 7 template library build the two steps with entirely
The degree of coupling of natural language querying process flow is more loose：Dictionary and template library can be in multiple query processings after once building completion
Middle Reusability；If specific area has existed suitable dictionary and template library in implementation process, can directly or slightly locate
It introduces and uses after reason, and without building from the beginning.Therefore, although dictionary and template library are the necessary components of this method,
But the process of structure dictionary and template library is more flexible in implementation process, therefore do not marked in flow chart shown in Fig. 1
Go out the two processes.However, dictionary and template library be using what kind of building process, as long as meeting method shown in Fig. 1 flows all
It should be regarded as protection scope of the present invention.
By above-mentioned steps, specific area, such as film relational database, search service just build and complete.
The search service make use of knowledge mapping technology, can support the natural language querying of user.Such as when user's in the embodiment
Which inquire about as " actor features the global earth 80 days ", the search service is with regard to that can directly give corresponding answer：" Cheng Long, flood
Treasure ... ".
The present invention provides a kind of database search method of knowledge based collection of illustrative plates, the method for implementing the technical solution
Many with approach, embodiment described above is only the preferred embodiment of the present invention.It should be pointed out that for the general of the art
For logical technical staff, various improvements and modifications may be made without departing from the principle of the present invention, these improve and
Retouching also should be regarded as protection scope of the present invention.The available prior art of each component being not known in the present embodiment is subject to reality
It is existing.
Claims (6)
1. a kind of database search method of knowledge based collection of illustrative plates, which is characterized in that including knowledge mapping structure and natural language
Two big step of query processing；
The knowledge mapping structure, including：
A. factor analysis is carried out to database, and table is divided into the pass of relation between the tables of data and storage object that store specific object
It is table, the element includes the restriction relation between table name, row name and table；
B. the record in tables of data and tables of data establishes concept node and entity node；Specially：To every in database
One tables of data TA, establish a concept node CA；Then for table TAIn each record TAi, establish an entity EAi,
And using each row name of this record and corresponding train value as the entity attributes and property value, then by concept node CAIt is directed toward real
Body node EAi, i is the sequence number of record；
C. according to the relation table of relation establishes the relation between entity node between foreign key constraint relation and storage object between tables of data；
Specially：If table TAIn row B be table TCThe external key of middle row D, then according to row B and the value correspondence of row D, establish table TAIn
Often row record TAiConstructed entity EAi, to table TCMiddle record TCjConstructed entity ECjBetween relation；If relation table TC
Store tables of data TATo TBMany-one relationship, then according to table TCThe Table A major key of record to table B major keys mapping relations, to build
Vertical table TAThe entity E of structureAiTo table TBThe entity E of structureBjBetween relation；
D. the relation between the node that is generated in the node and step c that are generated in step b is stored using knowledge mapping instrument,
Establish knowledge mapping service；
The natural language querying processing, including：
E. query statement input by user is segmented, and the vocabulary after participle is subjected to query elements mapping, inquired about
Feature schema and element value, the query elements include variable, relation, entity and concept；
F. feature schema is matched to obtain corresponding query pattern in template library；
G. element value is filled into query pattern and obtains knowledge mapping query statement；
H. knowledge mapping query statement is performed in knowledge mapping service and obtains the corresponding knowledge of user's inquiry.
2. the database search method of knowledge based collection of illustrative plates according to claim 1, which is characterized in that
To each tables of data T in databaseA, a concept node C is established with table name AA。
3. the database search method of knowledge based collection of illustrative plates according to claim 1, which is characterized in that
If table TAIn row B be table TCThe external key of middle row D, table TAIn often row record TAiConstructed entity EAiTo table TCMiddle note
Record TCjConstructed entity ECjBetween the title of relation determined according to the conceptual relation between table name A and C.
4. the database search method of knowledge based collection of illustrative plates according to claim 1, which is characterized in that
If relation table TCStore tables of data TATo TBMany-one relationship, table TAThe entity E of structureAiTo table TBThe entity of structure
EBjBetween the title of relation determined according to table name C.
5. the database search method of knowledge based collection of illustrative plates according to claim 1, which is characterized in that
Query statement input by user is segmented in step e, and the vocabulary after participle is subjected to query elements mapping, is obtained
The feature schema of inquiry and the method for element value include：
Using natural language processing segmentation methods to inquiry O={ o input by user1o2...on, o1o2...onFor individual character, carry out
Participle obtains word segmentation result W={ w1=o1o2...ok,w2=ok+1...,...,wN=om...on, segmenting the dictionary used includes
The relevant vocabulary of concept, entity, attribute and relation generated in general dictionary and step c；
Defined variable (Variable, V), relation (Relation, R), entity (Entity, E), four class of concept (Concept, C)
Query elements a, element each vocabulary in word segmentation result being mapped in the four classes query elements, are denoted as：＜ P, W
＞={ ＜ p1,w1＞, ＜ p2,w2＞ ... ＜ pN,wN＞ }, the element identification of each vocabulary mapping in word segmentation result is extracted
The feature schema of inquiry O is obtained, is denoted as：P={ p1,p2...pN},pi∈{V,R,E,C}。
6. the database search method of knowledge based collection of illustrative plates according to claim 5, which is characterized in that
Query pattern in the step f is denoted as X=f (V, R, E, C), and f (V, R, E, C) is the generalized function of four class elements, is
Knowledge mapping inquires about the combination of primitive and four class elements.
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