CN106204298A - Temporary social network under a kind of big data environment determines method and system - Google Patents
Temporary social network under a kind of big data environment determines method and system Download PDFInfo
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- CN106204298A CN106204298A CN201610556788.3A CN201610556788A CN106204298A CN 106204298 A CN106204298 A CN 106204298A CN 201610556788 A CN201610556788 A CN 201610556788A CN 106204298 A CN106204298 A CN 106204298A
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
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Abstract
Temporary social network under a kind of big data environment determines method, including: S1, determines the provisional of user property, determines the provisional of customer relationship, determine the provisional of user behavior；User property provisional for representing that user serves as certain social role the most temporarily；Customer relationship provisional for representing that the user in temporary social network has been the temporary social network that a certain temporary duty sets up composition, now customer relationship possesses provisional feature；User behavior provisional for representing that user is setting up interim social relations and after possessing interim social property, the social behavior being engaged in constitutes provisional feature；S2, carry out the part-time recommendation in job market, temporary identity find, user role migrate and user's occupation infer；Carry out temporary relation establishment and the detection of template activity territory；Carry out User Activity time, user's space position, user's provisional action and User Activity trajectory predictions.
Description
Technical field
The present invention relates to social networks studying technological domain, particularly to the temporary social network under a kind of big data environment
Determine method and system.
Background technology
Along with the fast development of social networks, social networks presents the various network structures come in every shape and network closes
System.Online social networks has been increasingly becoming and has connected disparate networks information and the indispensable tie of mankind's real world.To social activity
The depth profiling of network can help people to be better understood from behavioral pattern and the net of user in the structure mechanism of social networks, network
The evolutionary process of network structure.Wherein, group structure most basic in social networks has been done deeply by famous social balance theory
Annotation, simplest triangle relation is the three-legged structure in Undirected networks.Three-legged structure describes user in social networks and closes
Four kinds of structures of system, as shown in Figure 1.Fig. 1 gives the four kinds of probability combinations constructing friend and non-friends between user,
The relation that triple room is friendly or hostile is studied.But, the customer relationship in social networks is not only close friend or enemy
The simplest to relation.It is true that to setting up between the user of friends, when being affected by some factor and restricted, this
Kind seems firm customer relationship also can be broken (friend and non-friend can mutually convert) therewith.The present invention is with typical social
Network (Sina's microblogging, wechat and Twitter) is research platform, and the factor affecting user's transforming relationship is carried out induction and conclusion,
Study these factors are how to interfere the firm customer relationship of structure simultaneously.Thus, a kind of probability social networks is set up
Social balance theory has been carried out strong supplementing.Probability social networks is carried out based on the influence factor of user's transforming relationship
Modeling, can carry out quantification of targets to the intimate degree of customer relationship, can describe various index degree intimate to this quantization simultaneously
How to impact.
Currently, Chinese scholars has done a lot of related works for the research of field of social network.Now with grind herein
Study carefully closely-related research to summarize, mainly can be summarized as the following aspects:
The qualitative analysis of social network relationships: relate generally to user and set up association and geographical distribution, homogeneous relation, and
They customer relationships present in implicit interactions, the social balance theory.
Geographical distribution: in social networks, user behavior and geographical position present incidence relation, such as, based on microblog
Upper " mutual powder " relation divides to exist with the geographic area of people in actual life infers relation mutually.Social networks has broken real life
The geographical gap of people in work, the foundation of user-association will not excessively be limited by geographic factor.
Homogeneity: there is the social networks that the user of similar characteristic (sex, identity etc.) is more likely to set up to each other, i.e.
Social networks based on certain characteristic.It is further obvious that multilink incidence relation between user can make that link homogeneity shows,
And homogeneity of based on certain characteristic can be greatly reinforced the probability setting up incidence relation between user.
Implicit interactions: the extraction of implicit interactions comes from " mentioning " ("@") and " forwarding " behavior of user.Deposit when between user
When interactive (" mentioning " or " forwarding ") behavior, the probability setting up association between user will increase.
Social balance theory: the triangular close friend of main research or hostile relations.This theory is thought, " friend-friend-friend
Friend " social relations ratio " friend-friend-enemy " more conventional, the most stable.And the user setting up bilateral structure relation is formed
The likelihood ratio single-side structural of balanced structure is bigger.
The research of the rule of Guan Bi social networks mainly includes dynamic rule and the big class of propagated rule two.
The dynamic law of Guan Bi social networks: relate generally to user property and their corresponding network structure, and he
Corresponding social property.
User property: mainly include the check-ins (logining geographic location) of user, subscriber data, user interest
Point etc..These user properties can be made up of certain social network structure homogeneity, and this structure can be over time
Change and show the Changing Pattern of dynamic.Equally, the research that user property combines with geographical position is for structure social activity
The Guan Bi probability of network has certain directive significance.
The propagation law of Guan Bi social networks: can mutually produce impact between the closed user node of structure in social networks,
Then triangular closed propagation effect is formed.
But in prior art, in social networks, the short-term of customer relationship is set up and is released, user property and user behavior
Generations etc. can be affected by some factor (such as sponsor), and As time goes on cannot determine.
Summary of the invention
In view of this, the temporary social network under the present invention proposes a kind of big data environment determines method and system.
Temporary social network under a kind of big data environment determines method, and it comprises the steps:
S1, determine the provisional of user property, determine the provisional of customer relationship, determine the provisional of user behavior；With
Family attribute provisional for representing that user serves as certain social role the most temporarily；The provisional use of customer relationship
It has been the temporary social network that a certain temporary duty sets up composition, now user in the user represented in temporary social network
Relation possesses provisional feature；User behavior provisional for representing that user is being set up interim social relations and possessed interim
After social property, the social behavior being engaged in constitutes provisional feature；
S2, determine that result carries out the part-time recommendation in job market, temporary identity is sent out by the provisional of the user property in step S1
Existing, user role migrates and user's occupation is inferred；Provisional by the customer relationship in step S1 determines that result is carried out temporarily
Relation is set up and the detection of template activity territory；Provisional by the user behavior in step S1 determines that result carries out User Activity
Time, user's space position, user's provisional action and User Activity trajectory predictions.
Temporary social network under big data environment of the present invention determines in method,
Provisional for user property in described step S1, by time and space two dvielement in combination with getting up to analyze
And constitute temporary social network based on Spatio-temporal factors；And the quantity of active member is over time in this temporary social network
Change has increased and decreased；The structure derivation process of temporary social network meets periodically variable feature.
Temporary social network under big data environment of the present invention determines in method,
In described step S1, the matrix of temporary social network structure derivation process is expressed as follows: matrix 1 to matrix 4 follows
Ring:
Matrix 1
Matrix 2
Matrix 3
Matrix 4
Wherein, above-mentioned each matrix subscript S represents that sponsor, M represent perception medium, Ui, i=1...n represents interim group
Body member；MS,URepresent the matrix mapping relations between sponsor and group member, MS,M,URepresent sponsor and perception medium and group
Matrix mapping relations between body member, MM,URepresent the matrix mapping relations between perception medium and group member, RS→URepresent
Matrix ranks relation between sponsor and group member, RS,M→URepresent between sponsor and perception medium and group member
Matrix ranks relation, RM→URepresent the matrix ranks relation between perception medium and group member,Should
Value takes any value between 0-1, in order to describe each member of interim colony familiarity to each other.
Temporary social network under big data environment of the present invention determines in method, further comprising the steps of:
S3, determining the provisional of customer relationship according to the provisional of user property, provisional according to customer relationship determines
It is provisional that user behavior occurs；Simultaneously according to the provisional provisional to customer relationship of user behavior with user property is provisional
Infer.
The temporary social network that the present invention also provides under a kind of big data environment determines system, and it includes such as lower unit:
Determine unit, for determining the provisional of user property, determine the provisional of customer relationship, determine user behavior
Provisional；User property provisional for representing that user serves as certain social role the most temporarily；Customer relationship
Provisional for representing that the user in temporary social network has been the interim social network that a certain temporary duty sets up composition
Network, now customer relationship possesses provisional feature；User behavior provisional for representing that user is closed setting up interim society
After being and possessing interim social property, the social behavior being engaged in constitutes provisional feature；
Infer unit, determine that result carries out that job market is part-time to push away for the user property that is determined by unit provisional
Recommend, temporary identity finds, user role migrates and user's occupation is inferred；The customer relationship being determined by unit provisional really
Determine result and carry out temporary relation establishment and the detection of template activity territory；The provisional of the user behavior being determined by unit determines
Result carries out User Activity time, user's space position, user's provisional action and User Activity trajectory predictions.
Temporary social network under big data environment of the present invention determines in method,
Described determine in unit for user property provisional, by time and space two dvielement in combination with getting up point
Analyse and constitute temporary social network based on Spatio-temporal factors；And the quantity of active member is over time in this temporary social network
Change increased and decreased；The structure derivation process of temporary social network meets periodically variable feature.
Temporary social network under big data environment of the present invention determines in method,
Described determine that in unit, the matrix of temporary social network structure derivation process is expressed as follows: matrix 1 to matrix 4 is carried out
Circulation:
Matrix 1
Matrix 2
Matrix 3
Matrix 4
Wherein, above-mentioned each matrix subscript S represents that sponsor, M represent perception medium, Ui, i=1...n represents interim group
Body member；MS,URepresent the matrix mapping relations between sponsor and group member, MS,M,URepresent sponsor and perception medium and group
Matrix mapping relations between body member, MM,URepresent the matrix mapping relations between perception medium and group member, RS→URepresent
Matrix ranks relation between sponsor and group member, RS,M→URepresent between sponsor and perception medium and group member
Matrix ranks relation, RM→URepresent the matrix ranks relation between perception medium and group member,Should
Value takes any value between 0-1, in order to describe each member of interim colony familiarity to each other.
Temporary social network under big data environment of the present invention determines in method, also includes with lower unit:
Counter push away unit, for determining the provisional of customer relationship, according to customer relationship according to the provisional of user property
It is provisional that to determine that user behavior occurs provisional；Simultaneously according to user behavior provisional to customer relationship provisional and user
Attribute is provisional infers.
The temporary social network implemented under the big data environment that the present invention provides determines method and system and prior art phase
Than having the advantages that the short-term that can determine customer relationship in social networks is set up and released, user property and user
The generations of behavior etc. can be affected by some factor (such as sponsor), and As time goes on presents uncertain change
Rule, and contribute to being mutually distinguishable between the foundation of short-term social networks and each user of network internal.
Accompanying drawing explanation
Fig. 1 is four kinds of three-legged structure schematic diagrams in the Undirected networks of the embodiment of the present invention；
Fig. 2 is the temporary social network research system figure of the embodiment of the present invention；
Fig. 3 is the temporary social network structure derivation schematic diagram of the embodiment of the present invention；
Fig. 4 is the temporary social network structure derivation process schematic of the embodiment of the present invention；
Fig. 5 is situation key element and the user behavior provisional application schematic diagram of the embodiment of the present invention；
Fig. 6 is that the temporary social network under the big data environment of the embodiment of the present invention determines system architecture diagram.
Detailed description of the invention
If Fig. 2 is to shown in 6, show based on substantial amounts of achievement in research, the network structure of social networks can along with user behavior,
User property (personal attribute and social property), the change of customer relationship and the change of occurrence dynamics, this Changing Pattern thing
First cannot determine.Therefore, the existence of this phenomenon has led to the temporary relation of social networks.Data in temporary social network
Owing to data volume is big, data class various (track data, audio frequency, video, text etc.), data have real-time change, although
Can data therefrom be worth but the information value that can obtain before doing big data analysis and process is the lowest, due to the type number
According to meeting the 4V feature of big data, in temporary social network, therefore carry out data mining and analysis belong under big data environment,
Data mining and the research category of analysis decision.
Social networks provisional
The provisional of social networks is for user behavior, user property and customer relationship etc. and social network in social networks
The closely-related a series of research systems of network structure.User behavior can over time, place, personage, event, inducement etc. a series of
The change of situation key element and change.Although user property keeps stable over a period to come, once user behavior causes
The change of customer relationship, the most also can impact user property.So, have led to customer relationship periodically to become in time
The temporary social network problem changed and constantly construct.The provisional research of referred to as social networks in patent: facing of user behavior
Shi Xing, provisional and customer relationship provisional of user property, this three together constitutes the provisional research of social networks
System.The mutual relation of this research system and meaning are as shown in Figure 2.
As in figure 2 it is shown, the provisional concrete application scenarios of user property can recommendation part-time with job market, temporary identity be sent out
Existing, user role migrates and user's occupation deduction is associated.
User property provisional: be usually expressed as user and serve as certain social role, such as the most temporarily
Wedding celebration company meets parent driver, the service man of snack bar, the member of love and marriage website (century good hoddy, Bulbus Lilii net, treasure net etc.)
Etc..The social group at the social role place of these users has been configured to a social networks, and in these social networkies
The change over time of the quantity of active member has increased and decreased, and they are also equipped with provisional as the member in network simultaneously
Feature.It is to say, wedding celebration company connect parent drivers after meeting parent and terminating, their task the most just completes.And by wedding
This temporary social network that gift side is set up as sponsor is the most just dismissed automatically along with connecing completing of task of parent.Similarly,
The service man of snack bar is part-time, and love and marriage website members is also to seek a kind of temporary role of spouse in a short time, the most this kind of should
With together constituting temporary social network application.Therefore, the research to temporary social network can carry out interim part-time recommendation and
The temporary identity of user finds.When user is engaged in many parts of different part-time jobs, user role constitutes use at different part-time
The migration of family attribute.Thus, it is possible to the occupation being engaged in user carries out inferring the research of class.
If it addition, user property provisional by time and space two dvielement in combination with getting up to consider, just constitute
Temporary social network of based on Spatio-temporal factors.This kind of network has wide application prospect.Such as, multi-section wedding car performs to connect
During parent's task, owing to city vehicle is numerous, wedding car driver does not recognizes to each other mutually, and the wedding celebration outward appearance connecing parent's automobile is arranged the most very
Similar, if the different fleet of parent's task that connects of multiple execution is when the same area runs across, the most easily obscure.Therefore, for solving
This difficult problem, generally can by Jie Qin fleet constitute a temporary social network based on space-time key element, allow belong to same connect parent appoint
The fleet of business can show the GPS location of teammate's vehicle on the vehicle mounted guidance of each car in real time, be thus similar vehicle again
How also will not obscure or with losing.
It follows that will connect as a example by parent's task by wedding car, describe temporary social network in detail and dismiss whole development from being populated into
Some problem and the thinking of the problem of solution present in periodic process.
Wedding car meets the side of holding (bridegroom, bride and relatives thereof) of sponsor's typically wedding of parent's task.They can pass through
The mode of phone convenes a series of person of outstanding talent's car to serve as the wedding car connecing parent's task temporarily.Generally, due to the associated process of wedding car
Having randomness, therefore the structure of Hun Che fleet also has randomness, so this may result in Hun Che fleet driver each other it
Between mutually do not recognize.It follows that temporary social network structure derivation schematic diagram will be given, and connect as a example by parent's task in addition by wedding car
Illustrate, as shown in Figure 3.
From figure 3, it can be seen that the structure derivation process of temporary social network meets periodically variable feature.Fig. 3 (1)
In, sponsor can organize some the most unacquainted interim members jointly to complete task.In Fig. 3 (2), sponsor initiates
Interim member set up into the interim colony of the most unfamiliar Weak link (dotted line).In order to make mutual unfamiliar interim group
Member between body can jointly cooperate and be not directly contacted with, and can add perception medium between the member in interim colony.So far,
Interim social networks is collectively formed, as shown in Fig. 3 (3) between each member of sponsor and interim colony.When the time comes, interim group
Can be by perception medium in the case of not having sponsor to command between body, a certain task that jointly cooperated (such as, meets parent
Task).After task completes, interim colony dismisses therewith thus causes temporary social network to be disintegrated, and then returns to Fig. 3 (1) institute
The network structure state shown.
Customer relationship provisional: refer to the user in temporary social network and set up structure for completing a certain temporary duty
The temporary social network become, the most now customer relationship possesses provisional feature.Such as, certain held in scholar participating nation is academic
Meeting, they constitute an interim academic social networks within a certain period of time for academic exchange.Scholars in network
Constitute node, and between them, the behavior of the academic suggestion of exchange constructs connection limit each other.Scholars are as academic conference
Participant be exactly the provisional performance of customer relationship.
These scholars are carried out priori signature discovery, and they are before participating in academic conference, and their motion track has can
Can be from various parts of the country, but participate in academic conference those days, their motion track will be from respective residence
Gather in the region at place, host place of academic conference, thus easily user can be carried out casual user's relation
Research with the detection of template activity territory.
In order to describe the derivation process of the temporary social network structure shown in Fig. 3, it is also possible to by this figure with a matrix type
It is indicated and describes in detail, being illustrated in figure 4 the matrix method for expressing of temporary social network structure derivation process.
Figure 4, it is seen that Fig. 4 (1)-4 (4) and Fig. 3 (1)-3 (4) presents relation one to one, it describes sense
Know medium add before and after (including sponsor) relationship change situation between each member of social networks.Wherein, in Fig. 4 under above-mentioned each matrix
Footmark S represents that sponsor, M represent perception medium, Ui, i=1...n represents interim group member；MS,URepresent sponsor and colony
Matrix mapping relations between member, MS,M,URepresent the matrix mapping relations between sponsor and perception medium and group member,
MM,URepresent the matrix mapping relations between perception medium and group member, RS→URepresent the matrix between sponsor and group member
Ranks relation, RS,M→URepresent the matrix ranks relation between sponsor and perception medium and group member, RM→URepresent perception matchmaker
Matrix ranks relation between Jie and group member,This value takes any value between 0-1, uses
To describe each member of interim colony familiarity to each other.
User behavior provisional: refer to user after setting up interim social relations and possessing interim social property, from
The social behavior of thing constitutes provisional feature.Such as, scholars explain and publicise the recent research achievement of oneself in academic conference；Wedding
The courtship behavior etc. that love person is carried out by love and marriage website or TV love and marriage program, these user behaviors have provisional feature.
Therefore, the provisional feature of user behavior can be excavated, thus reach the situation key element of user's provisional action is carried
Refining and analysis, the purpose that user's provisional action is predicted.Usually, user's provisional action activity can be extracted such as Fig. 5 institute
The situation key element shown.
From figure 5 it can be seen that the provisional situation key element of user behavior generally can extract five: the time, personage, empty
Between, inducement and time.By the extraction to these five situation key elements, the prediction work of aspect provisional to user behavior can be completed
Make: the actual application of the aspects such as User Activity time, locus, provisional action and event trace.
By under big data environment, the detailed description of the periodicity derivation process of temporary social network structure can be seen
Going out, user property can determine the provisional of customer relationship, and the provisional of customer relationship foundation may result in what user behavior occurred
Provisional.Meanwhile, customer relationship and user property can be inferred by user behavior provisional in turn.Therefore, three
Between present close logical derivation relation.
As shown in Figure 6, the embodiment of the present invention also provides for the present invention and also provides for the interim social network under a kind of big data environment
Network determines system, and it includes such as lower unit:
Determine unit, for determining the provisional of user property, determine the provisional of customer relationship, determine user behavior
Provisional；User property provisional for representing that user serves as certain social role the most temporarily；Customer relationship
Provisional for representing that the user in temporary social network has been the interim social network that a certain temporary duty sets up composition
Network, now customer relationship possesses provisional feature；User behavior provisional for representing that user is closed setting up interim society
After being and possessing interim social property, the social behavior being engaged in constitutes provisional feature；
Infer unit, determine that result carries out that job market is part-time to push away for the user property that is determined by unit provisional
Recommend, temporary identity finds, user role migrates and user's occupation is inferred；The customer relationship being determined by unit provisional really
Determine result and carry out temporary relation establishment and the detection of template activity territory；The provisional of the user behavior being determined by unit determines
Result carries out User Activity time, user's space position, user's provisional action and User Activity trajectory predictions.
Temporary social network under big data environment of the present invention determines in method,
Described determine in unit for user property provisional, by time and space two dvielement in combination with getting up point
Analyse and constitute temporary social network based on Spatio-temporal factors；And the quantity of active member is over time in this temporary social network
Change increased and decreased；The structure derivation process of temporary social network meets periodically variable feature.
Temporary social network under big data environment of the present invention determines in method,
Described determine that in unit, the matrix of temporary social network structure derivation process is expressed as follows: matrix 1 to matrix 4 is carried out
Circulation:
Matrix 1
Matrix 2
Matrix 3
Matrix 4
Wherein, above-mentioned each matrix subscript S represents that sponsor, M represent perception medium, Ui, i=1...n represents interim group
Body member；MS,URepresent the matrix mapping relations between sponsor and group member, MS,M,URepresent sponsor and perception medium and group
Matrix mapping relations between body member, MM,URepresent the matrix mapping relations between perception medium and group member, RS→URepresent
Matrix ranks relation between sponsor and group member, RS,M→URepresent between sponsor and perception medium and group member
Matrix ranks relation, RM→URepresent the matrix ranks relation between perception medium and group member,Should
Value takes any value between 0-1, in order to describe each member of interim colony familiarity to each other.
Temporary social network under big data environment of the present invention determines in method, also includes with lower unit:
Counter push away unit, for determining the provisional of customer relationship, according to customer relationship according to the provisional of user property
It is provisional that to determine that user behavior occurs provisional；Simultaneously according to user behavior provisional to customer relationship provisional and user
Attribute is provisional infers.
It is understood that for the person of ordinary skill of the art, can conceive according to the technology of the present invention and do
Go out other various corresponding changes and deformation, and all these change all should belong to the protection model of the claims in the present invention with deformation
Enclose.
Claims (8)
1. the temporary social network under a big data environment determines method, it is characterised in that it comprises the steps:
S1, determine the provisional of user property, determine the provisional of customer relationship, determine the provisional of user behavior；User belongs to
Property provisional for representing that user serves as certain social role the most temporarily；Customer relationship provisional for table
Show that the user in temporary social network has been the temporary social network that a certain temporary duty sets up composition, now customer relationship
Possesses provisional feature；User behavior provisional for representing that user is setting up interim social relations and possess interim society
After attribute, the social behavior being engaged in constitutes provisional feature；
S2, determined that by the user property in step S1 provisional result carries out the part-time recommendation in job market, temporary identity finds, use
Family role migrates and user's occupation is inferred；Provisional by the customer relationship in step S1 determines that result carries out temporary relation group
Build and the detection of template activity territory；By the user behavior in step S1 provisional determine result carry out the User Activity time,
User's space position, user's provisional action and User Activity trajectory predictions.
2. the temporary social network under big data environment as claimed in claim 1 determines method, it is characterised in that
Provisional for user property in described step S1, by time and space two dvielement in combination with getting up to analyze and structure
Become temporary social network based on Spatio-temporal factors；And the quantity of active member change over time in this temporary social network
Increase and decrease；The structure derivation process of temporary social network meets periodically variable feature.
3. the temporary social network under big data environment as claimed in claim 2 determines method, it is characterised in that
In described step S1, the matrix of temporary social network structure derivation process is expressed as follows: matrix 1 to matrix 4 is circulated:
Matrix 1
Matrix 2
Matrix 3
Matrix 4
Wherein, above-mentioned each matrix subscript S represents that sponsor, M represent perception medium, Ui, i=1...n represents that interim colony becomes
Member；MS,URepresent the matrix mapping relations between sponsor and group member, MS,M,URepresent that sponsor becomes with perception medium and colony
Matrix mapping relations between Yuan, MM,URepresent the matrix mapping relations between perception medium and group member, RS→URepresent and initiate
Matrix ranks relation between people and group member, RS,M→URepresent the matrix between sponsor and perception medium and group member
Ranks relation, RM→URepresent the matrix ranks relation between perception medium and group member,I, j=1...n, this value takes Jie
Any value between 0-1, in order to describe each member of interim colony familiarity to each other.
4. the temporary social network under data environment as claimed in claim 3 big determines method, it is characterised in that also include with
Lower step:
S3, determining the provisional of customer relationship according to the provisional of user property, provisional according to customer relationship determines user
It is provisional that behavior occurs；Simultaneously according to the provisional provisional to customer relationship of user behavior with user property is provisional carries out
Infer.
5. the temporary social network under a big data environment determines system, it is characterised in that it includes such as lower unit:
Determine unit, for determining the provisional of user property, determine the provisional of customer relationship, determine the interim of user behavior
Property；User property provisional for representing that user serves as certain social role the most temporarily；Facing of customer relationship
Time property is used for representing that the user in temporary social network has been the temporary social network that a certain temporary duty sets up composition, this
Time customer relationship possess provisional feature；User behavior provisional for representing that user is setting up interim social relations and tool
After standby interim social property, the social behavior being engaged in constitutes provisional feature；
Infer unit, determine that result carries out the part-time recommendation in job market, faces for the provisional of user property being determined by unit
Time identity find, user role migrate and user's occupation infer；The provisional of the customer relationship being determined by unit determines knot
Fruit carries out temporary relation establishment and the detection of template activity territory；The provisional of the user behavior being determined by unit determines result
Carry out User Activity time, user's space position, user's provisional action and User Activity trajectory predictions.
6. the temporary social network under big data environment as claimed in claim 5 determines method, it is characterised in that
Described determine in unit for user property provisional, by time and space two dvielement in combination with getting up to analyze also
Constitute temporary social network based on Spatio-temporal factors；And the quantity of active member change over time in this temporary social network
Change and increased and decreased；The structure derivation process of temporary social network meets periodically variable feature.
7. the temporary social network under big data environment as claimed in claim 6 determines system, it is characterised in that
Described determine that in unit, the matrix of temporary social network structure derivation process is expressed as follows: matrix 1 to matrix 4 follows
Ring:
Matrix 1
Matrix 2
Matrix 3
Matrix 4
Wherein, above-mentioned each matrix subscript S represents that sponsor, M represent perception medium, Ui, i=1...n represents that interim colony becomes
Member；MS,URepresent the matrix mapping relations between sponsor and group member, MS,M,URepresent that sponsor becomes with perception medium and colony
Matrix mapping relations between Yuan, MM,URepresent the matrix mapping relations between perception medium and group member, RS→URepresent and initiate
Matrix ranks relation between people and group member, RS,M→URepresent the matrix between sponsor and perception medium and group member
Ranks relation, RM→URepresent the matrix ranks relation between perception medium and group member,I, j=1...n, this value takes Jie
Any value between 0-1, in order to describe each member of interim colony familiarity to each other.
8. the temporary social network under data environment as claimed in claim 7 big determines system, it is characterised in that also include with
Lower unit:
Counter push away unit, for determining the provisional of customer relationship according to the provisional of user property, interim according to customer relationship
It is provisional that property determines that user behavior occurs；Simultaneously according to user behavior provisional to customer relationship provisional and user property
Provisional infer.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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