CN110019694A - Method, apparatus and computer readable storage medium for knowledge mapping - Google Patents
Method, apparatus and computer readable storage medium for knowledge mapping Download PDFInfo
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- CN110019694A CN110019694A CN201710616130.1A CN201710616130A CN110019694A CN 110019694 A CN110019694 A CN 110019694A CN 201710616130 A CN201710616130 A CN 201710616130A CN 110019694 A CN110019694 A CN 110019694A
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract
The invention discloses a kind of method and apparatus for knowledge mapping, are related to big data technical field.This method comprises: determining the entity and incidence relation to be verified in knowledge mapping according to user demand；One or more associations entity is determined according to the entity to be verified and the incidence relation；Traverse path is generated according to the entity to be verified, the incidence relation and the associated entity；The knowledge mapping is traversed according to the traverse path, counts at least one in entity number, entity value and the attribute in the traverse path.This method and device can be improved the reliability of search efficiency and verification result.
Description
Technical field
The present invention relates to big data technical field, in particular to a kind of method, apparatus and computer for knowledge mapping
Readable storage medium storing program for executing.
Background technique
Big data processing technique is intended to arrive scale greatly in terms of acquisition, storage, management, analysis well beyond traditional data
The data acquisition system of library software means capability range is analyzed, is excavated, thus realize to these containing significant mass data into
Row specialized process.
By above-mentioned technical advantage, big data processing technique is widely applied to various fields, for example, in internet finance
In field, the prior art realizes intelligent air control by relevant database.But there are data redundancies for relevant database, no
It is easy to the disadvantages of doing association analysis, cause to have very big performance in terms of multi-source data cross validation and realizes bottleneck.
In order to effectively promote the performance of cross validation and association analysis, and greatly reduce the redundancy of data storage, base
It is applied in intelligent risk control in the knowledge mapping of big data technology building.Knowledge mapping can by visualization technique come
Knowledge resource and its carrier are described, and excavates, analyze, constructing, drawing and explicit knowledge and connecting each other between them.
Summary of the invention
The inventors found that above-mentioned exist in the prior art following problem: the prior art is mostly by knowledge graph
Simple keyword search is carried out in spectrum to be verified, and can not be accurately reflected the real demand of risk control rule, be caused to inquire
Low efficiency, verification result reliability are low.At least one problem in regarding to the issue above, present inventors have proposed solutions.
It is an object of the present invention to provide a kind of technical solution for knowledge mapping, with improve search efficiency and/or
The reliability of verification result.
According to one embodiment of present invention, a kind of method for knowledge mapping is provided, the knowledge mapping includes
Entity and relationship, the entity includes entity value and/or attribute, this method comprises: being determined in knowledge mapping according to user demand
Entity and incidence relation to be verified；One or more associations are determined according to the entity to be verified and the incidence relation
Entity；Traverse path is generated according to the entity to be verified, the incidence relation and the associated entity；According to the traversal
Knowledge mapping described in traversal path counts at least one in entity number, entity value and the attribute in the traverse path.
Optionally, the traverse path is using the entity to be verified as starting point, by all associated entities.
Optionally, the knowledge mapping constructs in the following manner: obtaining structural data, the knot from multiple information sources
It include at least one major key in structure data, the major key is used to indicate the corresponding pass between the structural data and entity
System；The entity for including in the structural data is extracted according to the major key；For the entity setting up marker, the marker
For identifying the type of the entity value；Data structure pair is generated according to the relationship between preset entity；Based on the data
Structure is to the generation knowledge mapping.
Optionally, the data structure is to for corpus separatum or by first instance, second instance and the pass between them
It is the triple constituted.
Optionally, after the entity for including in extracting the structural data, the useless number in the entity value is filtered out
According to.
Optionally, the entity of the data structure centering has attribute set, includes and the reality in the attribute set
The corresponding attribute of body.
According to another embodiment of the invention, a kind of device for knowledge mapping is provided, comprising: target determines mould
Block, for determining the entity and incidence relation to be verified in knowledge mapping according to user demand；Path-generating module is used for root
Determine one or more associations entity according to the entity to be verified and the incidence relation, according to the entity to be verified,
The incidence relation and the associated entity generate traverse path；Data statistics module, for being traversed according to the traverse path
The knowledge mapping counts at least one in entity number, entity value or the attribute in the traverse path.
Optionally, the traverse path is using the entity to be verified as starting point, by all associated entities.
Optionally, the knowledge mapping constructs in the following manner: obtaining structural data, the knot from multiple information sources
It include at least one major key in structure data, the major key is used to indicate the corresponding pass between the structural data and entity
System；The entity for including in the structural data is extracted according to the major key, filters out the hash in the entity value, and
Uniform format is carried out to the entity value according to preset data format；For the entity setting up marker, the marker is used
In the type for identifying the entity value；Data structure pair is generated according to the relationship between preset entity；It ties based on the data
Structure is to the generation knowledge mapping.
Optionally, the data structure is to for corpus separatum or by first instance, second instance and the pass between them
It is the triple constituted.
Optionally, the entity of the data structure centering has attribute set, includes and the reality in the attribute set
The corresponding attribute of body.
According to still another embodiment of the invention, a kind of device for knowledge mapping is provided, comprising: memory and coupling
It is connected to the processor of the memory, the processor is configured to holding based on the instruction being stored in the memory device
The method for knowledge mapping in any of the above-described a embodiment of row.
According to still another embodiment of the invention, a kind of computer readable storage medium is provided, computer is stored thereon with
Program, the program realize the method for knowledge mapping in any of the above-described a embodiment when being executed by processor.
Risk control is directed to an advantage of the present invention is that generating according to entity to be verified, incidence relation and associated entity
The traverse path of regular demand is made, and elements relevant to demand all in knowledge mapping are counted according to traverse path,
So that cross-validation process more meets user demand, to improve the reliability of search efficiency and/or verification result.
Detailed description of the invention
The attached drawing for constituting part of specification describes the embodiment of the present invention, and together with the description for solving
Release the principle of the present invention.
The present invention can be more clearly understood according to following detailed description referring to attached drawing, in which:
Fig. 1 shows the flow chart of one embodiment of the method for knowledge mapping of the invention.
Fig. 2 shows the flow charts of another embodiment of the method for knowledge mapping of the invention.
Fig. 3 shows the schematic diagram of one embodiment of traverse path of the invention.
Fig. 4 shows the schematic diagram of another embodiment of traverse path of the invention.
Fig. 5 shows the structure chart of one embodiment of the device for knowledge mapping of the invention.
Fig. 6 shows the structure chart of another embodiment of the device for knowledge mapping of the invention.
Specific embodiment
Carry out the various exemplary embodiments of detailed description of the present invention now with reference to attached drawing.It should also be noted that unless in addition having
Body explanation, the unlimited system of component and the positioned opposite of step, numerical expression and the numerical value otherwise illustrated in these embodiments is originally
The range of invention.
Simultaneously, it should be appreciated that for ease of description, the size of various pieces shown in attached drawing is not according to reality
Proportionate relationship draw.
Be to the description only actually of at least one exemplary embodiment below it is illustrative, never as to the present invention
And its application or any restrictions used.
Technology, method and apparatus known to person of ordinary skill in the relevant may be not discussed in detail, but suitable
In the case of, the technology, method and apparatus should be considered as authorizing part of specification.
It is shown here and discuss all examples in, any occurrence should be construed as merely illustratively, without
It is as limitation.Therefore, the other examples of exemplary embodiment can have different values.
It should also be noted that similar label and letter indicate similar terms in following attached drawing, therefore, once a certain Xiang Yi
It is defined in a attached drawing, then in subsequent attached drawing does not need that it is further discussed.
Fig. 1 shows the flow chart of one embodiment of the method for knowledge mapping of the invention.
Mainly comprising two kinds of elements of relationship between entity and entity in knowledge mapping.Entity may include entity name
And entity value.For example, entity name can be " people ", corresponding entity value can be ID card No..In another example entity name
It can be " phone ", corresponding entity value can be specific telephone number.Relationship is used to describe the related information between entity,
Such as the relationship between entity " people " and entity " phone " can be " personal contact method ".Entity can also have one or more
A attribute is described, for example, entity " people " can have attribute " gender: male " and " name: Zhang San ".
As shown in Figure 1, knowledge mapping can be constructed by step 110-150.
In step 110, structural data is obtained from multiple information sources.It include at least one major key in structural data,
Major key is used to indicate the corresponding relationship between structural data and entity (or attribute).The source of structural data can be hand and fill out
Data, device data (such as address list, message registration, GPS location data etc.), carrier data and online shopping data etc..
In one embodiment, structural data is for example are as follows:
String person_id:110212198503213141；
Int age:32；
String personal_phone:+86-177-0108-7572；
String home_address: Dongcheng District, Beijing during March milky way SOHO D2.
There are 4 major keys, respectively person_id, personal_phone, home_address in the structural data
And age.
In the step 120, the entity for including in structural data is extracted according to major key.For example, major key person_id,
Personal_phone and home_address can respectively correspond 3 class entities, that is, people, phone and address.According to major key and reality
The corresponding relationship of body extracts the entity in structural data, available 3 entities " people: 110212198503213141 ", " electricity
Words :+86-177-0108-7572 " and " address: Dongcheng District, Beijing during March milky way SOHO D2 ".It can also be according to major key from structure
Change in data and extracts attribute.For example, the attribute " age " of major key age correspondent entity " people ", is closed according to major key is corresponding with attribute
System extracts the attribute in structural data, available attribute " age: 32 ".
Since structural data can derive from different data sources, wherein there may be hash, Er Qietong
The format of categorical data often disunity.Therefore, in one embodiment, the entity for including in extracting the structural data
Afterwards, the hash in entity value can be filtered out.For example, the telephone number for being, nothing can will repeatedly be marked
Effect address or the entity value not obviously being inconsistent with entity value data type are judged as hash, and are filtered.
Uniform format can also be carried out to the entity value according to preset data format.For example, being obtained from different data sources
The entity value of the entity " phone " taken may be that "+86-177-0108-7572 " is also likely to be " 17701087572 ", can be by lattice
Formula is unified for one of the two.Also it can specify that the entity value length (such as larger than 10 words) of entity " address ", with full name shape
Formula indicates provinces and cities district (as " Beijing " are unified for " Beijing "), and dispenses unit and doorplate (such as will " cell 7 inwardly
1 unit 2301 " of building is reduced to " No. 7 building of cell inwardly ").By above-mentioned data cleansing process, melting for multi-source data can be improved
Close efficiency and data user rate.
In addition, since structural data can may deposit the same entity from many different data sources
In different entity values.For example, reality can be extracted from the structural data obtained from two electric business websites in Jingdone district and Taobao
Body " account ", corresponding entity value are respectively " 123456 " and " 654321 ".In this case, entity value is 6 bit digitals, but
Represent different meanings.
It in response to this, in step 130, is entity setting up marker.For example, setting marker@JD and@TB difference
Represent Jingdone district and Taobao.After marker is arranged, entity is " account :@JD 123456 " and " account :@TB 654321 ".Thus
It can guarantee that the type of the corresponding entity value of different types of data is also different, to improve the search efficiency of knowledge mapping, make
Obtaining multi-source data can preferably merge.
In step 140, data structure pair is generated according to the relationship between preset entity.
In one embodiment, according to extract 3 entities " people: 110212198503213141 ", " phone :+
The personal electricity of triple " people "-can be generated in 86-177-0108-7572 " and " address: Dongcheng District, Beijing during March milky way SOHO D2 "
Words-" phone " and triple " people "-home address-" address ".Personal call and home address in triple are relationship.Data
Structure is to single entity is also possible to, for example, temporarily not having " people " of any relationship with other entities.
Attribute set can be added for the entity of data structure centering.For example, attribute " year can be added for entity " people "
Age: 32 ".Such as " name: Zhang San ", " gender: male ", " marital status: unmarried " attribute can also be added in attribute set.
In step 150, based on data structure to generation knowledge mapping.Above-mentioned triple or single entities can be deposited
Storage is updated into knowledge mapping.For example, by entity and relationship storage into storaging medium.If having existed the reality before
Body or relationship, then according to preset more new strategy (for example, can be indicated according to the time field of structural data successive suitable
Sequence) it updates into storaging medium.
In above-described embodiment, by the way that marker and data cleaning process is arranged for entity value, multi-source data can be improved and melt
The efficiency and utilization rate of conjunction, improve the cross validation performance of multi-source data, to improve the practical value of knowledge mapping.
Fig. 2 shows the flow charts of another embodiment of the method for knowledge mapping of the invention.
As shown in Fig. 2, can realize the cross validation of information in knowledge mapping by executing step 210-230.
In step 210, the entity and incidence relation to be verified in knowledge mapping is determined according to user demand.
In one embodiment, user demand be verify certain loan application people address list in phone which is appeared in its
In the address list of his loan application people, whether the overdue loan ratio of these loan applications people is more than 50%.
Fig. 3 shows the schematic diagram of one embodiment of traverse path of the invention.As shown in figure 3, according to user demand, it can
To determine that the entity to be verified in knowledge mapping is that " people: A " (for A as entity value, specifically can be such as identification card number can generation
The value of table person part), incidence relation is " address list ".Arrow in Fig. 3 can be with the direction of relationship between presentation-entity.For example,
There is telephone number a in the address list of loan application people A1, then the arrow of relationship " address list " is directed toward entity by entity " people: A "
" phone: a1”。
In a step 220, one or more associations entity is determined according to entity and incidence relation to be verified.
It in one embodiment, can as shown in figure 3, according to entity " people: A " to be verified and incidence relation " address list "
To determine that associated entity corresponding with user demand includes the entity " phone: a for having address list relationship with entity " people: A "1”、
" phone: a2" and " phone: a3”(a1-a3Can be telephone number), and there is address list relationship with above three telephone number
Entity " people: B ", " people: C " and " people: D " (value of these three entity attributes " whether applying providing a loan " is "Yes", otherwise not
Meet user demand).
In step 230, traverse path is generated according to entity to be verified, incidence relation and associated entity.For example, traversal
Path is using entity to be verified as starting point, by all associated entities.
In one embodiment, as shown in figure 3, the starting point of traverse path can be the entity to be verified that user directly pays close attention to
" people: A ", and pass through all associated entities " phone: a1", " phone: a2", " phone: a3", " people: B ", " people: C " and " people: D ".
The traverse path reflects following fact: 3 telephone number a are shared in the address list of loan application people A1、a2And a3, these three
At least one of telephone number has appeared in the address list of loan application people B, C and D.
In step 240, knowledge mapping is traversed according to traverse path, entity number, entity value in statistics traverse path
With at least one in attribute.
For example, in traverse path as shown in Figure 3, " people " entity for meeting user demand shares 3: B, C and D.System
Count the value of these three entity attributes " whether loan is overdue ", it is known that it is wherein overdue to have 2: B and C, it has been more than sum
50%.Therefore judge that the corresponding loan application people A of entity " people: A " has touched risk control rule, statistical result is returned
User.
In another embodiment, user demand is to verify: providing the multidigit of the home phone number of certain loan application people
Other loan applications people (for example, with the same household to provide a loan of certain loan application people), each provides the family of certain loan application people
Whether the home address in front yard address, these different information sources is identical.
Fig. 4 shows the schematic diagram of another embodiment of traverse path of the invention.As shown in figure 4, according to user demand
Can determine that entity to be verified is " people: A ", incidence relation include " home phone number ", " home address ", " provide phone " and
" address is provided ".Arrow in Fig. 4 can be with the direction of relationship between presentation-entity.For example, the home address of loan application people A is
B, then the arrow of relationship " home address " is directed toward entity " address: b " by entity " people: A ".
According to entity and incidence relation to be verified can determine associated entity include " people: B ", " people: C ", people: D ", " electricity
Words: a ", " address: b " and " address: c ".The entity " people: A " to be verified that traverse path is primarily upon with user is starting point, warp
Cross above-mentioned all associated entities.That is, traverse path describes following fact: loan application people B, C and D are each provided with loan
The home phone number a of money applicant A, and each provide the home address b and c of loan application people A.
Found after statistics, entity " people: B ", " people: C " and people in traverse path: D " provide A home address have b
The entity value different with c two.That is, as shown in figure 4, with entity " people: A " have the having of home address relationship " address: b " and
" address: c " two different entities.Therefore judge that the corresponding loan application people A of entity " people: A " has touched risk control rule,
The statistical result is returned into user.
In addition, since the structural data for generating knowledge mapping is probably derived from many different data sources, for example, same
Personal phone number may be simultaneously from multiple data such as hand number completion evidence, device data, carrier data, online shopping data
Source.In view of the situation, it needs to verify between separate sources data with the presence or absence of unmatched problem.For example, it is desired to verify logical
Data in news record whether with carrier data there are Chong Die, in online shopping data posting address, addressee's phone whether with
There is overlapping etc. in the data that hand number completion evidence, operator and the address list at family provide.
For example, (can such as derive from user to the same data from different data sources during being counted
Address list and same telephone number from operator) carry out non-repetition counting, to guarantee that obtained statistical result is accurate.?
Foundation of Duplication of the same data in different data source as cross validation can be counted, thus map of enriching one's knowledge
Application scenarios.Statistics may include counting, summing, averaging.
In above-described embodiment, based on the entity to be verified, incidence relation and associated entity that are determined according to user demand,
Generate the traverse path of knowledge mapping.And entity, the attribute in path are counted, so that cross-validation process meets user
Risk control rule demand, to improve the reliability of search efficiency and verification result.
Fig. 5 shows the structure chart of one embodiment of the device for knowledge mapping of the invention.
As shown in figure 5, the device includes: target determination module 51, path-generating module 52 and data statistics module 53.
Target determination module 51 determines the entity and incidence relation to be verified in knowledge mapping according to user demand.Example
Such as, target determination module 51 can execute the step 210 in above-described embodiment.
In one embodiment, the knowledge mapping used can carry out structure by the method in any of the above-described a embodiment
It builds, detailed process repeats no more in the present embodiment.
Path-generating module 52 determines one or more associations entity according to entity and incidence relation to be verified, according to
Entity, incidence relation and the associated entity of verifying generate traverse path.For example, traverse path is using entity to be verified as starting point,
By all associated entities.For example, path-generating module 52 can execute the step 220 in above-described embodiment.
Data statistics module 53 traverses knowledge mapping according to traverse path, entity number, entity in statistics traverse path
At least one of in value or attribute.For example, data statistics module 53 can execute the step 230 in above-described embodiment.
In above-described embodiment, the traverse path of knowledge mapping is generated according to the demand of user, and to entity therein, attribute
It is counted, and result is returned into user, so that cross-validation process meets the risk control rule demand of user, to improve
The reliability of search efficiency and verification result.
Fig. 6 shows the structure chart of another embodiment of the device for knowledge mapping of the invention.
As shown in fig. 6, the device 60 of the embodiment includes: memory 61 and the processor for being coupled to the memory 61
62, processor 62 is configured as executing in the present invention in any one embodiment based on the instruction being stored in memory 61
Method for knowledge mapping.
Wherein, memory 61 is such as may include system storage, fixed non-volatile memory medium.System storage
Such as be stored with operating system, application program, Boot loader (Boot Loader), database and other programs etc..
Those skilled in the art should be understood that the embodiment of the present invention can provide as method, system or computer journey
Sequence product.Therefore, complete hardware embodiment, complete software embodiment or combining software and hardware aspects can be used in the present invention
The form of embodiment.Moreover, it wherein includes the calculating of computer usable program code that the present invention, which can be used in one or more,
Machine can use the meter implemented in non-transient storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of calculation machine program product.
So far, the method, apparatus according to the present invention for knowledge mapping is described in detail and computer-readable deposits
Storage media.In order to avoid covering design of the invention, some details known in the field are not described.Those skilled in the art
As described above, completely it can be appreciated how implementing technical solution disclosed herein.
Method and system of the invention may be achieved in many ways.For example, can by software, hardware, firmware or
Software, hardware, firmware any combination realize method and system of the invention.The said sequence of the step of for the method
Merely to be illustrated, the step of method of the invention, is not limited to sequence described in detail above, special unless otherwise
It does not mentionlet alone bright.In addition, in some embodiments, also the present invention can be embodied as to record program in the recording medium, these programs
Including for realizing machine readable instructions according to the method for the present invention.Thus, the present invention also covers storage for executing basis
The recording medium of the program of method of the invention.
Although some specific embodiments of the invention are described in detail by example, the skill of this field
Art personnel it should be understood that above example merely to being illustrated, the range being not intended to be limiting of the invention.The skill of this field
Art personnel are it should be understood that can without departing from the scope and spirit of the present invention modify to above embodiments.This hair
Bright range is defined by the following claims.
Claims (14)
1. a kind of method for knowledge mapping, the knowledge mapping includes entity and relationship, the entity include entity value and/
Or attribute, which comprises
The entity and incidence relation to be verified in knowledge mapping is determined according to user demand；
One or more associations entity is determined according to the entity to be verified and the incidence relation；
Traverse path is generated according to the entity to be verified, the incidence relation and the associated entity；
The knowledge mapping is traversed according to the traverse path, counts entity number, entity value and the category in the traverse path
Property at least one of.
2. method according to claim 1, wherein the traverse path is using the entity to be verified as starting point, warp
Cross all associated entities.
3. method according to claim 1, wherein the knowledge mapping constructs in the following manner:
Structural data is obtained from multiple information sources, includes at least one major key in the structural data, the major key is used for
Indicate the corresponding relationship between the structural data and entity；
The entity for including in the structural data is extracted according to the major key；
For the entity setting up marker, the marker is used to identify the type of the entity value；
Data structure pair is generated according to the relationship between preset entity；
Structure is to the generation knowledge mapping based on the data.
4. according to the method described in claim 3, wherein, the data structure is to for corpus separatum or by first instance, second
The triple that entity and the relationship between them are constituted.
5. according to the method described in claim 3, further include:
After the entity for including in extracting the structural data, the hash in the entity value is filtered out.
6. according to the method described in claim 3, further include:
Uniform format is carried out to the entity value according to preset data format.
7. according to the described in any item methods of claim 3-6, wherein the entity of the data structure centering has property set
It closes, includes attribute corresponding with the entity in the attribute set.
8. a kind of device for knowledge mapping, the knowledge mapping includes entity and relationship, the entity include entity value and/
Or attribute, described device include:
Target determination module, for determining the entity and incidence relation to be verified in knowledge mapping according to user demand；
Path-generating module, for determining one or more associations reality according to the entity to be verified and the incidence relation
Body generates traverse path according to the entity to be verified, the incidence relation and the associated entity；
Data statistics module counts the reality in the traverse path for traversing the knowledge mapping according to the traverse path
At least one of in body number, entity value or attribute.
9. device according to claim 8, wherein the traverse path is passed through using the entity to be verified as starting point
All associated entities.
10. device according to claim 8, wherein the knowledge mapping constructs in the following manner:
Structural data is obtained from multiple information sources, includes at least one major key in the structural data, the major key is used for
Indicate the corresponding relationship between the structural data and entity；
The entity for including in the structural data is extracted according to the major key, filters out the hash in the entity value,
And uniform format is carried out to the entity value according to preset data format；
For the entity setting up marker, the marker is used to identify the type of the entity value；
Data structure pair is generated according to the relationship between preset entity；
Structure is to the generation knowledge mapping based on the data.
11. device according to claim 10, wherein the data structure is to for corpus separatum or by first instance,
The triple that two entities and the relationship between them are constituted.
12. according to the described in any item devices of claim 8-11, wherein the entity of the data structure centering has property set
It closes, includes attribute corresponding with the entity in the attribute set.
13. a kind of device for knowledge mapping, comprising:
Memory；And
It is coupled to the processor of the memory, the processor is configured to based on the finger being stored in the memory device
It enables, executes such as the method for any of claims 1-7 for knowledge mapping.
14. a kind of computer readable storage medium, is stored thereon with computer program, realized such as when which is executed by processor
Method of any of claims 1-7 for knowledge mapping.
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| CN201710616130.1A CN110019694A (en) | 2017-07-26 | 2017-07-26 | Method, apparatus and computer readable storage medium for knowledge mapping |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110609888A (en) * | 2019-09-24 | 2019-12-24 | 北京明略软件系统有限公司 | Map verification method, device, server and storage medium based on relational network |
| CN111274410A (en) * | 2020-01-21 | 2020-06-12 | 北京明略软件系统有限公司 | Data storage method and device and data query method and device |
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