CN105095306A - Operating method and device based on associated objects - Google Patents
Operating method and device based on associated objects Download PDFInfo
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- CN105095306A CN105095306A CN201410213865.6A CN201410213865A CN105095306A CN 105095306 A CN105095306 A CN 105095306A CN 201410213865 A CN201410213865 A CN 201410213865A CN 105095306 A CN105095306 A CN 105095306A
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Abstract
The invention discloses an operating method and device based on associated objects. The operating method based on associated objects comprises: obtaining the attribute information of a plurality of objects and obtaining correlation information between any two objects according to the attribute information; performing clustering processing on the plurality of objects according to the correlation information to obtain the information of the associated objects; and performing corresponding operations according to the information of the associated objects. The operating method based on associated objects is capable of identifying all the associated objects to guide users to operate correctly and reasonably; as a result, the use experience of the users or the transaction security of a third-party mechanism is enhanced; besides, the operating method is wide in application range and simple to implement.
Description
Technical field
The application relates to field of computer technology, particularly relates to a kind ofly to carry out the method that operates and device based on affiliated partner.
Background technology
Shopping online, is exactly by Internal retrieval merchandise news, and sends purchase request by electronic purchase order, then paid the bill by the mode such as Alipay or bank card, and last manufacturer is delivered by the mode of mailordering, or by process that express company delivers goods to the customers.
Along with popularizing of internet, the advantage of shopping at network is more outstanding, day by day becomes a kind of important shopping form.But before carrying out shopping online, usually need the member becoming this website, but same user likely can register multiple member based on a variety of causes, then multiple members of same user's registration belong to same entity, and namely these members are association members.
At present, identify that the method for association member generally identifies its relevance according to some attribute information between two members, and, direct binary relation can only be identified.Such as, if member A and member B is identified on the first attribute information is same entity, B and C is identified on the second attribute information is same entity, but it is same entity that current scheme None-identified goes out A and C, thus cannot based on real association member carry out correct, reasonably operate.
Summary of the invention
The application is intended to solve one of technical matters in correlation technique at least to a certain extent.For this reason, an object of the application be to propose a kind of can identify whole affiliated partner and user can be guided to carry out correctly, reasonably operation carry out the method that operates and device based on affiliated partner.
A kind of method of carrying out operating based on affiliated partner that the embodiment of the present application provides, comprising: the attribute information obtaining multiple object, obtains the degree of correlation information between any two objects according to described attribute information; According to described degree of correlation information, clustering processing is carried out to described multiple object, obtain the information of affiliated partner; And operate accordingly according to the information of described affiliated partner.
Above-mentioned embodiment of the method for carrying out operating based on affiliated partner, by obtaining the attribute information of multiple object, obtains the degree of correlation information between any two objects according to described attribute information; And according to described degree of correlation information, clustering processing is carried out to described multiple object, obtain the information of affiliated partner; Then operate accordingly according to the information of described affiliated partner, whole affiliated partner can be identified, thus user can be guided to carry out correctly, reasonably operating, improve the experience of user or the transaction security of the third-party institution, applied range and realize simple.
A kind of device carrying out operating based on affiliated partner that the embodiment of the present application provides, comprising: acquisition module, for obtaining the attribute information of multiple object, obtains the degree of correlation information between any two objects according to described attribute information; Cluster module, for carrying out clustering processing according to described degree of correlation information to described multiple object, obtains the information of affiliated partner; And operational module, for operating accordingly according to the information of described affiliated partner.
Above-mentioned device embodiment of carrying out operating based on affiliated partner, obtains the attribute information of multiple object by acquisition module, obtain the degree of correlation information between any two objects according to described attribute information; And according to described degree of correlation information, clustering processing is carried out to described multiple object by cluster module, obtain the information of affiliated partner; Then operated accordingly by the information of operational module according to described affiliated partner, whole affiliated partner can be identified, thus user can be guided to carry out correctly, reasonably operating, improve the experience of user or the transaction security of the third-party institution, applied range and realize simple.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of the identification affiliated partner of the application's embodiment.
Fig. 2 be the application's embodiment carry out based on affiliated partner the method flow diagram that operates.
Fig. 3 be another embodiment of the application carry out based on affiliated partner the method flow diagram that operates.
Fig. 4 is the structural representation carrying out the device operated based on affiliated partner of the application's embodiment.
Embodiment
Be described below in detail the embodiment of the application, the example of described embodiment is shown in the drawings, and wherein same or similar label represents same or similar element or has element that is identical or similar functions from start to finish.Be exemplary below by the embodiment be described with reference to the drawings, be intended to for explaining the application, and the restriction to the application can not be interpreted as.
What below with reference to the accompanying drawings describe the embodiment of the present application carries out the method that operates and device based on affiliated partner.
Fig. 1 is the process flow diagram of the identification affiliated partner of the application's embodiment.
As shown in Figure 1, the process of this identification affiliated partner comprises:
S101, obtains the attribute information of multiple object, obtains the degree of correlation information between any two objects according to attribute information.
In this embodiment, object can be member etc.; Wherein, the attribute information of object can including, but not limited to the ID (identity number) card information of member, Alipay account, industrial and commercial registration number, cell-phone number etc.
Wherein, can take the degree of correlation information between any two objects of multiple matched rule acquisition, degree of correlation information herein can be the probability that two objects belong to same entity.Such as can determine that these two objects belong to the probability of same entity by the matched rule corresponding according to the ID (identity number) card information of two objects, also can determine that these two objects belong to the probability of same entity according to the industrial and commercial registration of a two objects number matched rule corresponding with cell-phone number, etc.
After determining that two objects belong to the probability of same entity, can be converted into the distance between these two objects, the probability that two objects belong to same entity is higher, and the distance between these two objects is less.Particularly, conversion formula can be adopted the probability that two objects belong to same entity to be converted to distance between these two objects, and wherein, conversion formula is:
D(x,y)＝min(dis(x
k,y
k))＝min((|(c
k*p(x
k,y
k)-1|)/1)
D (x, y) represents the distance between object x and y, p (x
k, y
k) represent that object belongs to the probability of same entity under matched rule k, c
kbe regulation coefficient, represent the intensity of matched rule k, particularly, c
kcan be 1,0.9 or 0.85 etc.
S102, carries out clustering processing according to degree of correlation information to multiple object, obtains the information of affiliated partner.
In this embodiment, Agglomerative Hierarchical Clustering algorithm can be used to carry out clustering processing to multiple object according to the distance between two objects, other clustering algorithms also can be adopted to carry out clustering processing to multiple object.
Wherein, Agglomerative Hierarchical Clustering algorithm is a kind of bottom-up strategy, first using each object as one bunch, then merge these bunches for increasing bunch, until all objects are all in one bunch, or meet certain finish condition.In Agglomerative Hierarchical Clustering algorithm, the most classical algorithm is AGNES algorithm, and in step S101, why by the probability that two objects belong to same entity, the distance be converted between these two objects is exactly to adopt AGNES algorithm.If the distance between an object in an object in bunch C1 and bunch C2 is minimum in Euclidean distance between all objects belonging to different bunches, then C1 and C2 may be merged.This is a kind of single connection method, its each bunch can by bunch in all objects represent, the similarity between two bunches is determined by the similarity that the data point that these two bunches of middle distances are nearest is right.
AGNES algorithm can be described as:
Input: N number of object, end condition is that the distance between any two bunches is greater than predetermined threshold
Export: M bunch
(1) each object is treated as an initial cluster
(2) (Repeat) is repeated
(3) nearest two bunches are found according to data point nearest in two bunches
(4) merge two bunches, generate the set of new bunch
(5) until (Until) meets end condition
Particularly, the distance between following bunch of range formula compute cluster can be adopted:
D(clustei,clustej)＝min(D(cluste
in,cluster
jm))
Wherein, D (cluste
in, cluster
jm) representing the distance in object n and bunch j between object m in bunch i, object n and m is equivalent to object x and y in S101.
As can be seen here, if the distance between object n and m in bunch i and bunch j is 0, be less than hypothesis predetermined threshold 0.03, then bunch i and bunch j can be merged into one new bunch, the distance until between the object of any two bunches after being arranged in merging is more than or equal to till 0.03.
It should be noted that, 0.03 example being only predetermined threshold, this predetermined threshold also can be other numerical value, such as 0,0.1 etc.
For example, there are now A, B, C, D tetra-objects, the distance knowing between object A and B according to the attribute information of these four objects is 0, distance between object C and D is also 0, then determine that object A and B belongs to bunch 1, object C and D belongs to bunches 2, and the distance then calculated between object B and C is also 0, and the distance namely between bunch 1 and bunches 2 is 0, then will bunch 1 and bunch 2-in-1 and be bunches 3, then object A, B, C, D in bunches 3 belong to same entity.
It should be noted that, affiliated partner belongs to the situation of same entity except comprising multiple object, can also comprise multiple object and have other incidence relations.
The process of above-mentioned identification affiliated partner, by obtaining the attribute information of multiple object, obtains the degree of correlation information between any two objects according to attribute information; Then according to degree of correlation information, clustering processing is carried out to multiple object, obtain the information of affiliated partner, thus identify whole affiliated partner, and realize simple.
Fig. 2 be the application's embodiment carry out based on affiliated partner the method flow diagram that operates.
As shown in Figure 2, the method should carrying out operating based on affiliated partner comprises:
S201, obtains the attribute information of multiple object, obtains the degree of correlation information between any two objects according to attribute information.
Wherein, the details that realizes of S201 can be identical with S101, do not repeat herein.
S202, carries out clustering processing according to degree of correlation information to multiple object, obtains the information of affiliated partner.
Wherein, the details that realizes of S202 can be identical with S102, do not repeat herein.
S203, the information according to affiliated partner operates accordingly.
After determining that multiple object belongs to same entity, associative operation can also be carried out as required.Such as, after the multiple objects determining to belong to same entity deliver many shopping evaluation informations, the evaluation information of repetition can be deleted to only remaining one or two evaluation informations, to evade the unreasonable operation of illegal businessman, guarantee validity and the authenticity of evaluation information, there is provided effective reference for user buys commodity, improve the buying experience of user.
In addition, after determining to belong to multiple objects of same entity, the information that these objects belong to same entity can also be shown, so that user is according to information identification shopping evaluation information or the authenticity of other information and validity, the business that the third-party institution is corresponding according to this information process can also be made, such as, same user have registered multiple on-line shop in Taobao, and these on-line shops have different attribute datas, such as shop name is different, telephone number is different etc., when these on-line shops are to certain credit agency's apply for loan, if this credit agency does not know that these on-line shops belong to same user, it may be then the loan limit that each on-line shop authorizes 50,000, if but this credit agency knows that these on-line shops belong to same user, it may be then the loan limit that each on-line shop authorizes 20,000, to reduce the risk that this user cannot refund, improve the service security of oneself.
It should be noted that, above-mentioned credit agency is only example, and the object that the determination of the embodiment of the present application belongs to same entity can be applied in different fields, different industries, and realizes simple.
Above-mentioned embodiment of the method for carrying out operating based on affiliated partner, by obtaining the attribute information of multiple object, obtains the degree of correlation information between any two objects according to attribute information; And according to degree of correlation information, clustering processing is carried out to multiple object, obtain the information of affiliated partner, thus whole affiliated partner can be identified, then operate accordingly according to the information of affiliated partner, improve the authenticity of information, validity and transparency, thus user can be guided to carry out correctly, reasonably operating, improve the experience of user or the transaction security of the third-party institution, applied range and realize simple.
Fig. 3 be another embodiment of the application carry out based on affiliated partner the method flow diagram that operates.As shown in Figure 3, the method comprises:
S301, obtains the attribute information of multiple object, belongs to the probability of same entity, be then converted into the distance between corresponding two objects according to any two objects of attribute information acquisition.
Assuming that, in this embodiment, obtain the ID (identity number) card information of member 1, Alipay account, industrial and commercial registration number respectively, the ID (identity number) card information of member 2, cell-phone number, the industrial and commercial registration of member No. 3, cell-phone number, the cell-phone number of member 4, the ID (identity number) card information of member 5.
Then, the first corresponding according to ID (identity number) card information matched rule determines that the probability that member 1 and member 2 belong to same entity is 1, c
kbeing 1, is then 0 according to the conversion formula provided in the S101 distance calculated between member 1 and member 2; Second matched rule corresponding according to cell-phone number determines that the probability that member 3 and member 4 belong to same entity is 1, c
kbeing 0.85, is then 0.15 according to the conversion formula provided in the S101 distance calculated between member 3 and member 4; It is 1, c that first matched rule corresponding according to ID (identity number) card information determines that member 1 and member 5 belong to same entity probability
kbeing 1, is then 0 according to the conversion formula provided in the S101 distance calculated between member 1 and member 5.
S302, uses Agglomerative Hierarchical Clustering algorithm to carry out clustering processing to multiple object according to the distance between any two objects, obtains the information of affiliated partner.
Assuming that predetermined threshold is 0.2, then member 1 and 2 belongs to bunch 1, member 3 and 4 belongs to bunches 2, member 1 and 5 belongs to bunches 3, and the distance that bunch range formula using S102 to provide calculates between bunch 1 and bunches 3 is 0, the distance 0 between bunch 1 and bunches 2, because the distance between the member 1 being arranged in bunch 1 and the member 3 being arranged in bunches 2 is 0, then bunch 1-3 can merge into one new bunch, and the member comprised in this new bunch belongs to same entity, and namely member 1-5 belongs to same entity.
S303, the information according to association member operates accordingly.
After determining that member 1-5 belongs to same entity, find 100 evaluation informations that current site has member 1-5 to deliver same Shopping content, its objective is the quantity in order to increase favorable comment information, improve the attention rate of user, this commodity are bought to guide user, but after adopting the method for the embodiment of the present application to determine that member 1-5 belongs to same entity, 99 evaluation informations can be deleted and namely only retain 1 evaluation information, to guarantee the authenticity of evaluation information, there is provided effective reference for user buys commodity, improve the satisfaction of user.
Above-mentioned embodiment of the method for carrying out operating based on affiliated partner, by obtaining the attribute information of multiple object, obtains the degree of correlation information between any two objects according to attribute information; And according to degree of correlation information, clustering processing is carried out to multiple object, obtain the information of affiliated partner; Then operate accordingly according to the information of affiliated partner, improve the authenticity of information, validity and transparency, for user operation provides effective foundation, improve the experience of user.
In order to realize above-described embodiment, the application also proposes a kind of device carrying out operating based on affiliated partner.
Fig. 4 is the structural representation carrying out the device operated based on affiliated partner of the application's embodiment.
As shown in Figure 4, the device that should carry out operating based on affiliated partner comprises: acquisition module 41, cluster module 42 and operational module 43, wherein:
Acquisition module 41, for obtaining the attribute information of multiple object, obtains the degree of correlation information between any two objects according to above-mentioned attribute information; Cluster module 42, for carrying out clustering processing according to above-mentioned degree of correlation information to above-mentioned multiple object, obtains the information of affiliated partner; Operational module 43 is for operating accordingly according to the information of above-mentioned affiliated partner.
Above-mentioned object can be member etc.; Wherein, the attribute information of object can including, but not limited to the ID (identity number) card information of member, Alipay account, industrial and commercial registration number, cell-phone number etc.
Above-mentioned acquisition module 41 can comprise: determining unit 411 and converting unit 412, wherein: determining unit 411 is for determining that according to the attribute information of two objects above-mentioned two objects belong to the probability of same entity; Converting unit 412 is converted to the distance between above-mentioned two objects for the probability that above-mentioned two objects are belonged to same entity.
Particularly, determining unit 411 can determine that these two objects belong to the probability of same entity by the matched rule corresponding according to the ID (identity number) card information of two objects, also can determine that these two objects belong to the probability of same entity according to the industrial and commercial registration of a two objects number matched rule corresponding with cell-phone number, etc.Converting unit 412 can adopt conversion formula that the probability that above-mentioned two objects belong to same entity is converted to the distance between above-mentioned two objects, and wherein, above-mentioned conversion formula is:
D(x,y)＝min(dis(x
k,y
k))＝min((|(c
k*p(x
k,y
k)-1|)/1)
D (x, y) represents the distance between object x and y, p (x
k, y
k) represent that object belongs to the probability of same entity under matched rule k, c
kbe regulation coefficient, represent the intensity of matched rule k.
In addition, above-mentioned cluster module 42 may be used for: use Agglomerative Hierarchical Clustering algorithm to carry out clustering processing to above-mentioned multiple object according to the distance between above-mentioned two objects, obtain at least one affiliated partner bunch.Further, when the number of above-mentioned affiliated partner bunch is greater than for the moment, the distance between the object being arranged in any two affiliated partners bunch is greater than predetermined threshold.Namely the object being less than or equal to predetermined threshold is all arranged in same cluster.
Further, aforesaid operations module 43 may be used for: determine to belong to multiple objects of same entity according to the information of above-mentioned affiliated partner after, and display corresponding objects belongs to the information of same entity and/or deletes the evaluation information of the repetition that above-mentioned same entity is delivered.
Such as, after the multiple objects determining to belong to same entity deliver many shopping evaluation informations, the evaluation information of repetition can be deleted to only remaining one or two evaluation informations, to evade the unreasonable operation of illegal businessman, guarantee validity and the authenticity of evaluation information, there is provided effective reference for user buys commodity, improve the buying experience of user.
In addition, after determining to belong to multiple objects of same entity, the information that these objects belong to same entity can also be shown, so that user is according to information identification shopping evaluation information or the authenticity of other information and validity, the business that the third-party institution is corresponding according to this information process can also be made, such as, same user have registered multiple on-line shop in Taobao, and these on-line shops have different attribute datas, such as shop name is different, telephone number is different etc., when these on-line shops are to certain credit agency's apply for loan, if this credit agency does not know that these on-line shops belong to same user, it may be then the loan limit that each on-line shop authorizes 50,000, if but this credit agency knows that these on-line shops belong to same user, it may be then the loan limit that each on-line shop authorizes 20,000, to reduce the risk that this user cannot refund, improve the service security of oneself.
It should be noted that, above-mentioned credit agency is only example, and the object that the determination of the embodiment of the present application belongs to same entity can be applied in different fields, different industries, and realizes simple.
Above-mentioned device embodiment of carrying out operating based on affiliated partner, obtains the attribute information of multiple object by acquisition module, obtain the degree of correlation information between any two objects according to above-mentioned attribute information; And according to above-mentioned degree of correlation information, clustering processing is carried out to above-mentioned multiple object by cluster module, obtain the information of affiliated partner, thus whole affiliated partner can be identified; Then operated accordingly by the information of operational module according to above-mentioned affiliated partner, improve the authenticity of information, validity and transparency, thus user can be guided to carry out correctly, reasonably operating, improve the experience of user or the transaction security of the third-party institution, applied range and realize simple.
In the description of this instructions, at least one embodiment that specific features, structure, material or feature that the description of reference term " embodiment ", " some embodiments ", " example ", " concrete example " or " some examples " etc. means to describe in conjunction with this embodiment or example are contained in the application or example.In this manual, to the schematic representation of above-mentioned term not must for be identical embodiment or example.And the specific features of description, structure, material or feature can combine in one or more embodiment in office or example in an appropriate manner.In addition, when not conflicting, the feature of the different embodiment described in this instructions or example and different embodiment or example can carry out combining and combining by those skilled in the art.
In addition, term " first ", " second " only for describing object, and can not be interpreted as instruction or hint relative importance or imply the quantity indicating indicated technical characteristic.Thus, be limited with " first ", the feature of " second " can express or impliedly comprise at least one this feature.In the description of the application, the implication of " multiple " is at least two, such as two, three etc., unless otherwise expressly limited specifically.
Describe and can be understood in process flow diagram or in this any process otherwise described or method, represent and comprise one or more for realizing the module of the code of the executable instruction of the step of specific logical function or process, fragment or part, and the scope of the preferred implementation of the application comprises other realization, wherein can not according to order that is shown or that discuss, comprise according to involved function by the mode while of basic or by contrary order, carry out n-back test, this should understand by the embodiment person of ordinary skill in the field of the application.
In flow charts represent or in this logic otherwise described and/or step, such as, the sequencing list of the executable instruction for realizing logic function can be considered to, may be embodied in any computer-readable medium, for instruction execution system, device or equipment (as computer based system, comprise the system of processor or other can from instruction execution system, device or equipment instruction fetch and perform the system of instruction) use, or to use in conjunction with these instruction execution systems, device or equipment.With regard to this instructions, " computer-readable medium " can be anyly can to comprise, store, communicate, propagate or transmission procedure for instruction execution system, device or equipment or the device that uses in conjunction with these instruction execution systems, device or equipment.The example more specifically (non-exhaustive list) of computer-readable medium comprises following: the electrical connection section (electronic installation) with one or more wiring, portable computer diskette box (magnetic device), random access memory (RAM), ROM (read-only memory) (ROM), erasablely edit ROM (read-only memory) (EPROM or flash memory), fiber device, and portable optic disk ROM (read-only memory) (CDROM).In addition, computer-readable medium can be even paper or other suitable media that can print described program thereon, because can such as by carrying out optical scanning to paper or other media, then carry out editing, decipher or carry out process with other suitable methods if desired and electronically obtain described program, be then stored in computer memory.
Should be appreciated that each several part of the application can realize with hardware, software, firmware or their combination.In the above-described embodiment, multiple step or method can with to store in memory and the software performed by suitable instruction execution system or firmware realize.Such as, if realized with hardware, the same in another embodiment, can realize by any one in following technology well known in the art or their combination: the discrete logic with the logic gates for realizing logic function to data-signal, there is the special IC of suitable combinational logic gate circuit, programmable gate array (PGA), field programmable gate array (FPGA) etc.
Those skilled in the art are appreciated that realizing all or part of step that above-described embodiment method carries is that the hardware that can carry out instruction relevant by program completes, described program can be stored in a kind of computer-readable recording medium, this program perform time, step comprising embodiment of the method one or a combination set of.
In addition, each functional unit in each embodiment of the application can be integrated in a processing module, also can be that the independent physics of unit exists, also can be integrated in a module by two or more unit.Above-mentioned integrated module both can adopt the form of hardware to realize, and the form of software function module also can be adopted to realize.If described integrated module using the form of software function module realize and as independently production marketing or use time, also can be stored in a computer read/write memory medium.
The above-mentioned storage medium mentioned can be ROM (read-only memory), disk or CD etc.Although illustrate and described the embodiment of the application above, be understandable that, above-described embodiment is exemplary, can not be interpreted as the restriction to the application, and those of ordinary skill in the art can change above-described embodiment, revises, replace and modification in the scope of the application.
Claims (12)
1. carry out the method operated based on affiliated partner, it is characterized in that, comprising:
Obtain the attribute information of multiple object, obtain the degree of correlation information between any two objects according to described attribute information;
According to described degree of correlation information, clustering processing is carried out to described multiple object, obtain the information of affiliated partner; And
Information according to described affiliated partner operates accordingly.
2. method according to claim 1, is characterized in that, described according to the degree of correlation information between any two objects of described attribute information acquisition, comprising:
Determine that described two objects belong to the probability of same entity according to the attribute information of two objects; And
The probability that described two objects belong to same entity is converted to the distance between described two objects.
3. method according to claim 2, is characterized in that, the described distance be converted to by the probability that described two objects belong to same entity between described two objects, comprising:
The probability that described two objects belong to same entity is converted to the distance between described two objects by employing conversion formula, and wherein, described conversion formula is:
D(x,y)＝min(dis(x
k,y
k))＝min((|(c
k*p(x
k,y
k)-1|)/1)
D (x, y) represents the distance between object x and y, p (x
k, y
k) represent that object belongs to the probability of same entity under matched rule k, c
kbe regulation coefficient, represent the intensity of matched rule k.
4. method according to claim 2, is characterized in that, describedly carries out clustering processing according to described degree of correlation information to described multiple object, obtains the information of affiliated partner, comprising:
Use Agglomerative Hierarchical Clustering algorithm to carry out clustering processing to described multiple object according to the distance between described two objects, obtain at least one affiliated partner bunch.
5. method according to claim 4, is characterized in that, when the number of described affiliated partner bunch is greater than for the moment, the distance between the object being arranged in any two affiliated partners bunch is greater than predetermined threshold.
6. the method according to the arbitrary claim of claim 1-5, is characterized in that, the described information according to described affiliated partner operates accordingly, comprising:
Determine to belong to multiple objects of same entity according to the information of described affiliated partner after, display corresponding objects belongs to the information of same entity and/or deletes the evaluation information of the repetition that described same entity is delivered.
7. carry out the device operated based on affiliated partner, it is characterized in that, comprising:
Acquisition module, for obtaining the attribute information of multiple object, obtains the degree of correlation information between any two objects according to described attribute information;
Cluster module, for carrying out clustering processing according to described degree of correlation information to described multiple object, obtains the information of affiliated partner; And
Operational module, for operating accordingly according to the information of described affiliated partner.
8. device according to claim 7, is characterized in that, described acquisition module, comprising:
Determining unit, for determining that according to the attribute information of two objects described two objects belong to the probability of same entity; And
Converting unit, the probability for described two objects are belonged to same entity is converted to the distance between described two objects.
9. device according to claim 8, is characterized in that, described converting unit, specifically for:
The probability that described two objects belong to same entity is converted to the distance between described two objects by employing conversion formula, and wherein, described conversion formula is:
D(x,y)＝min(dis(x
k,y
k))＝min((|(c
k*p(x
k,y
k)-1|)/1)
D (x, y) represents the distance between object x and y, p (x
k, y
k) represent that object belongs to the probability of same entity under matched rule k, c
kbe regulation coefficient, represent the intensity of matched rule k.
10. device according to claim 8, is characterized in that, described cluster module, specifically for:
Use Agglomerative Hierarchical Clustering algorithm to carry out clustering processing to described multiple object according to the distance between described two objects, obtain at least one affiliated partner bunch.
11. devices according to claim 10, is characterized in that, when the number of described affiliated partner bunch is greater than for the moment, the distance between the object being arranged in any two affiliated partners bunch is greater than predetermined threshold.
12. devices according to the arbitrary claim of claim 7-11, is characterized in that, described operational module, specifically for:
Determine to belong to multiple objects of same entity according to the information of described affiliated partner after, display corresponding objects belongs to the information of same entity and/or deletes the evaluation information of the repetition that described same entity is delivered.
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| CN108121737A (en) * | 2016-11-29 | 2018-06-05 | 阿里巴巴集团控股有限公司 | A kind of generation method, the device and system of business object attribute-bit |
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