CN101887573A - Social network clustering correlation analysis method and system based on core point - Google Patents
Social network clustering correlation analysis method and system based on core point Download PDFInfo
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Abstract
The invention provides social network clustering correlation analysis method and system based on a core point. The method comprises the following steps of: acquiring a stable time period of a social network; carrying out approximation on the social network at the stable time period to obtain a social network approximation graph; solving maximal cliques in the social network approximation graph; carrying out merging on the maximal cliques to obtain leagues according to the proportion of common points among the maximal cliques in the corresponding maximal cliques; and correlating leagues at different moments according to the similarity. In the invention, the approximation is carried out on the social network at the acquired stable time period, and the approximation method can effectively reduce the influence of noise on the subsequent analysis, simultaneously retains the basic features of the social network and ensures that the analysis result is more accurate. In the process of discovering the leagues, the invention directly carries out the merging on the maximal cliques, can rapidly discover the leagues and further rapidly acquire the analysis result.
Description
Technical field
The present invention relates to social network clustering correlation analysis method and system based on core point.
Background technology
At present the object handled of data mining task mainly is independent data instance, and these data instances often can represent with a vector that comprises a plurality of property values, simultaneously between these data instances hypothesis be on the statistics independently.For example, train a disease diagnosing system, its task is whether subject of diagnosis suffers from certain infectious disease, common way is to represent a subject with a vector, suppose that simultaneously the ill situation between each subject is separate, know that promptly making a definite diagnosis patient for one can not provide any help for other subjects of diagnosis are whether ill.Experience directly perceived is told us this hypothesis is irrational, and a people's relative, friend suffer from this infectious disease, then he other people have bigger possibility ill relatively.In society, the person to person simply adds up independently sampled point, is certainly existing contact and influence between them, has ignored this contact meeting the performance of whole diagnostic system is brought very big influence.In order to address this problem, the relation between the data instance must be taken into account simultaneously, thereby proposed the notion of community network, can portray social structure with graph structure.
Community network comprises a lot of nodes and one or more specific links that are connected these nodes.Wherein, node has often been represented the entity that physics such as individual, group, people, article and/or server exist; The various relations that exist between the node are then represented in link, as friends, kinship, trade relations, adduction relationship etc.Community network also has the expression mode of other sociology forms and quantic except graph structure is represented.
Under many circumstances, link need be analyzed the community network situation of change in a period of time the analysis of community network so along with the time constantly changes, and at present, mainly is that to carry out piecewise analysis behind the branches such as time period that will analyze be incremental analysis.Yet, in actual conditions, the generation development of things is not uniform, incremental analysis method can't accurately analyze noise and the incident in the community network, wherein, noise is meant and the social network analysis theme is irrelevant gets in touch, and mainly by the randomness of the individual behavior with socialization feature and uncertain causing, for example misdials and the invalid conversation that causes; Incident is meant unusually get in touch relevant with the social network analysis theme, for example conversation of people during the Spring Festival.Incremental analysis method, on the one hand, may in analytic process, amplify noise, perhaps often can't catch the evolution point (incident) that in this time period things development is produced great change, thereby can't provide accurate analytical results, how to obtain accurate analytical results apace, directly influence the efficient of social network analysis.
Summary of the invention
Therefore, the object of the present invention is to provide social network clustering correlation analysis method and system, obtain accurate analytical results apace based on core point.
For realizing above-mentioned purpose of the present invention, a kind of social network clustering correlation analysis method and system based on core point is provided, comprising:
Obtain the stationary time section of community network;
Community network to the stationary time section is similar to, and obtains the community network approximate diagram;
Obtain the very big group in the described community network approximate diagram;
Proportion according to the shared corresponding very big group of total point between the very big group carries out merger with described very big group, obtains corporations;
According to similarity, related different corporations constantly.
Preferably, described community network to the stationary time section is similar to and comprises:
Initialization abortive haul network;
Limit collection ordering with the community network of described stationary time section;
In order the limit collection is added in the described abortive haul network,, obtain the community network approximate diagram of described stationary time section until the deviation minimum of the community network of described abortive haul network and described stationary time section.
Preferably, described clooating sequence is a descending.
Preferably, described basis is the proportion of the shared corresponding very big group of total point between the group greatly, described very big group is carried out merger comprise:
When two very big the counting when subtracting N more than or equal to the counting of few very big group of counting of total point between the group, with these two greatly group's merger, wherein, N is for greater than 0 integer less than few very big blob number of counting.
Preferably, described N is 1.
Preferably, described similarity comprises the some registration of corporations and/or the similarity of structure.
Preferably, also comprise:
Analyze the tightness degree of described corporations structure;
And/or, analyze the degree of uniformity of limit weight distribution between the inner each point of described corporations.
The present invention also provides a kind of social network clustering correlation analysis method and system based on core point, it is characterized in that this system comprises:
Steady unit is used to obtain the stationary time section of community network;
Approximate unit is used for the community network of stationary time section is similar to, and obtains the community network approximate diagram;
Computing unit is used for obtaining the very big group of described community network approximate diagram;
The corporations unit is used for according to the proportion that greatly has the shared corresponding very big group of point between the group described very big group being carried out merger, obtains corporations;
Tracing unit is used for according to similarity, related different corporations constantly.
Preferably, described approximate unit comprises:
The initialization subelement is used for initialization abortive haul network;
The ordering subelement is used for the limit collection ordering with the community network of described stationary time section;
Approximate subelement is used in order the limit collection being added described abortive haul network, until the deviation minimum of the community network of described abortive haul network and described stationary time section, obtains the community network approximate diagram of described stationary time section.This system also comprises:
Analytic unit is used to analyze the tightness degree of described corporations structure; And/or, analyze the degree of uniformity of limit weight distribution between the inner each point of described corporations.
The invention has the beneficial effects as follows:
The present invention is similar to the community network of the stationary time section that obtains, and this approximate method can effectively reduce the influence of noise in subsequent analysis, has also kept the essential characteristic of community network simultaneously, makes analysis result more accurate.On the basis of community network approximate diagram, adopt the method for asking for of greatly rolling into a ball and merger, find corporations; With the core point of corporations as follow-up cluster association, and in the process of finding corporations, directly very big group is carried out merger, more greatly roll into a ball with respect to prior art, set up the greatly incidence relation between the group, greatly roll into a ball the mode of merging according to incidence relation according to comparative result, technical scheme of the present invention has been saved the space of a large amount of storage incidence relations, and avoided repeatedly comparing before the merger, can find corporations apace, and then obtain analysis result apace.
Description of drawings
Fig. 1 illustrates in the embodiment of the invention schematic flow sheet based on the social network clustering correlation analysis method of core point;
Fig. 2 illustrates in the embodiment of the invention application flow synoptic diagram based on the social network clustering correlation analysis method of core point;
Fig. 3 illustrates the community network approximate construction synoptic diagram of stationary time section in the embodiment of the invention;
Fig. 4 illustrates the structural representation of greatly rolling into a ball in the embodiment of the invention;
Fig. 5 illustrates the structural representation that corporations are followed the trail of in the embodiment of the invention;
Fig. 6 illustrates in the embodiment of the invention structural representation based on the social network clustering correlation analysis system of core point.
Embodiment
Describe social network clustering correlation analysis method and system based on core point of the present invention in detail below in conjunction with accompanying drawing.For fear of noise, the present invention adopts the approximate diagram structure to portray the community network of steady evolutionary phase.
See also Fig. 1, a kind of social network clustering correlation analysis method and system based on core point comprise:
Obtain the stationary time section of community network;
Community network to the stationary time section is similar to, and obtains the community network approximate diagram;
Obtain the very big group in the described community network approximate diagram;
Proportion according to the shared corresponding very big group of total point between the very big group carries out merger with described very big group, obtains corporations;
According to similarity, related different corporations constantly.
Described community network to the stationary time section is similar to and comprises:
Initialization abortive haul network;
Limit collection ordering with the community network of described stationary time section;
In order the limit collection is added in the described abortive haul network,, obtain the community network approximate diagram of described stationary time section until the deviation minimum of the community network of described abortive haul network and described stationary time section.
Preferably, described clooating sequence is a descending.
Preferably, described basis is the proportion of the shared corresponding very big group of total point between the group greatly, described very big group is carried out merger comprise:
When two very big the counting when subtracting N more than or equal to the counting of few very big group of counting of total point between the group, with these two greatly group's merger, wherein, N is for greater than 0 integer less than few very big blob number of counting.
Preferably, described N is 1.
On the basis of community network approximate diagram, adopt the method for asking for of greatly rolling into a ball and merger, find corporations; With the core point of corporations as follow-up cluster association, and in the process of finding corporations, directly very big group is carried out merger, more greatly roll into a ball with respect to prior art, set up the greatly incidence relation between the group, greatly roll into a ball the mode of merging according to incidence relation according to comparative result, technical scheme of the present invention has been saved the space of a large amount of storage incidence relations, and avoided repeatedly comparing before the merger, can find corporations apace, and then obtain analysis result apace.
Preferably, described similarity comprises the some registration of corporations and/or the similarity of structure.
Preferably, also comprise:
Analyze the tightness degree of described corporations structure;
And/or, analyze the degree of uniformity of limit weight distribution between the inner each point of described corporations.
The evolution of community network is a process steady and incident alternately occurs.By incident (evolutionary point) is taken place in the feature extraction of the community network of former and later two stationary time sections, contrast their differences in these two time periods, thereby accurately find the generation of incident in the network evolution process fast, and disclose this incident influence that network evolution produced.
See also Fig. 2, the social network clustering correlation analysis method based on core point carried out applicating example:
201, data: the community network data of accepting user's input;
202, the stationary time section is approximate: adopt heuristic, abortive haul network of initialization, then the limit collection of network is pressed descending sort, and constantly join in the network in order, the network after the feasible increase limit and the deviation minimum of the network of this time period, obtain the approximate diagram of this time period at last, for example, see also Fig. 3, the first network 301-1, the second network 301-2, the 3rd network 301-3 and the 4th network 301-4 are respectively four networks according to time order and function, they belong to same stationary time section, and approximate diagram 302 is the approximate diagram of this time period;
Corporations find to comprise:
203, look for clique (very big complete subgraph among the figure, promptly greatly group): for given approximate diagram, find out all clique, for example, see also Fig. 4, has two clique, be respectively 1,2,4,5} with 2,3,4};
204, assembling section clique: to any two clique that common point is arranged, if its common point number reaches the size-1 (value of size is the node number in the very big group) of a clique less among these two clique, these two clique just merge so.This step iteration operation does not take place until there being clique to merge once more.
205, divide overlapping node: give wherein certain corporation overlapping node division, obtain non-overlapped corporations;
206, absorb special joint: original not node in certain corporation is absorbed;
207, merge tight corporations: the corporations that merge tight association.
208, corporations are followed the trail of: be directed to the different corporations that find constantly, consider the some registration of corporations and the similarity of structure, they are associated, for example, please participate in Fig. 5, d figure is the most similar to a figure;
209, corporations develop: according to the corporations that track, from following two aspects the character of corporations is estimated: a) tightness degree of corporations' structure; B) degree of uniformity of limit weight distribution between the inner each point of corporations.
The method that existing corporations find, because it is at the incidence relation (whether having k-1 common point) that carries out will setting up before clique merges between clique, and the foundation of this relation need be carried out the repeatedly comparison between clique.More and related closely the time when clique structure among the figure, can influence the efficient of this method greatly; Also need to preserve the relation between a large amount of clique simultaneously, thereby cause a large amount of expenses of internal memory.
This programme adopts consolidation strategy immediately in the process that corporations find, improved combined efficiency and saved memory cost simultaneously, has improved analysis speed.
The present invention also provides a kind of social network clustering correlation analysis method and system based on core point, it is characterized in that this system comprises:
Steady unit is used to obtain the stationary time section of community network;
Approximate unit is used for the community network of stationary time section is similar to, and obtains the community network approximate diagram;
Computing unit is used for obtaining the very big group of described community network approximate diagram;
The corporations unit is used for according to the proportion that greatly has the shared corresponding very big group of point between the group described very big group being carried out merger, obtains corporations;
Tracing unit is used for according to similarity, related different corporations constantly.
Preferably, described approximate unit comprises:
The initialization subelement is used for initialization abortive haul network;
The ordering subelement is used for the limit collection ordering with the community network of described stationary time section;
Approximate subelement is used in order the limit collection being added described abortive haul network, until the deviation minimum of the community network of described abortive haul network and described stationary time section, obtains the community network approximate diagram of described stationary time section.This system also comprises:
Analytic unit is used to analyze the tightness degree of described corporations structure; And/or, analyze the degree of uniformity of limit weight distribution between the inner each point of described corporations.
Although abovely describe the present invention in detail, to those skilled in the art, under the teaching of this paper, can make various modifications and distortion, and not break away from the spirit and scope of the invention the present invention with reference to embodiment.
Claims (10)
1. social network clustering correlation analysis method and system based on a core point comprise:
Obtain the stationary time section of community network;
Community network to the stationary time section is similar to, and obtains the community network approximate diagram;
Obtain the very big group in the described community network approximate diagram;
Proportion according to the shared corresponding very big group of total point between the very big group carries out merger with described very big group, obtains corporations;
According to similarity, related different corporations constantly.
2. method according to claim 1, wherein, described community network to the stationary time section is similar to and comprises:
Initialization abortive haul network;
Limit collection ordering with the community network of described stationary time section;
In order the limit collection is added in the described abortive haul network,, obtain the community network approximate diagram of described stationary time section until the deviation minimum of the community network of described abortive haul network and described stationary time section.
3. method according to claim 2, wherein, described clooating sequence is a descending.
4. method according to claim 1, wherein, described basis is the proportion of the shared corresponding very big group of total point between the group greatly, described very big group is carried out merger comprise:
When two very big the counting when subtracting N more than or equal to the counting of few very big group of counting of total point between the group, with these two greatly group's merger, wherein, N is for greater than 0 integer less than few very big blob number of counting.
5. method according to claim 4, wherein, described N is 1.
6. method according to claim 1, wherein, described similarity comprises the some registration of corporations and/or the similarity of structure.
7. method according to claim 6 wherein, also comprises:
Analyze the tightness degree of described corporations structure;
And/or, analyze the degree of uniformity of limit weight distribution between the inner each point of described corporations.
8. social network clustering correlation analysis method and system based on a core point is characterized in that this system comprises:
Steady unit is used to obtain the stationary time section of community network;
Approximate unit is used for the community network of stationary time section is similar to, and obtains the community network approximate diagram;
Computing unit is used for obtaining the very big group of described community network approximate diagram;
The corporations unit is used for according to the proportion that greatly has the shared corresponding very big group of point between the group described very big group being carried out merger, obtains corporations;
Tracing unit is used for according to similarity, related different corporations constantly.
9. system according to claim 8 is characterized in that, described approximate unit comprises:
The initialization subelement is used for initialization abortive haul network;
The ordering subelement is used for the limit collection ordering with the community network of described stationary time section;
Approximate subelement is used in order the limit collection being added described abortive haul network, until the deviation minimum of the community network of described abortive haul network and described stationary time section, obtains the community network approximate diagram of described stationary time section.
10. according to Claim 8 or 9 described systems, it is characterized in that this system also comprises:
Analytic unit is used to analyze the tightness degree of described corporations structure; And/or, analyze the degree of uniformity of limit weight distribution between the inner each point of described corporations.
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Application publication date: 20101117 |