A Topic Community Mining Method for Online Social Networks
A social network and community mining technology, applied in the field of online social network services, can solve problems such as being unsuitable for practical applications and complex mining process, and achieve the effect of mining quality assurance and good mining quality.
Active Publication Date: 2018-12-21
ZHONGKAI UNIV OF AGRI & ENG +1
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Problems solved by technology
In general, the above topic community mining methods have the following problems: different models need to be designed for user node link information and content information, and the community mining process needs to be divided into multiple stages, which makes the mining process too complicated and not suitable for practical use. application
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Embodiment Construction
[0038] Combine below figure 2 An example of an online social network is shown to illustrate a specific embodiment of the method of the present invention.
[0039] Step 1: Formally represent online social networks. Formally express the online social network example as G=(V,E,T), where V=(v 0 ,v 1 ,v 2 ,v 3 ,v 4 ,v 5 ,v 6 ,v 7 ),
[0040] E={e 01 ,e 04 ,e 12, e 24 ,e 34 ,e 45 ,e 56 ,e 57,e 67}, T={social network, big data}, n=8, m=2.
[0041] Step 2: Build user node link matrix and subject feature word association matrix According to V and E, X can be obtained as:
[0042]
[0043] For Y, it is necessary to calculate the feature vectors of the topic feature words associated with each user node in turn. Take user node v 4 For example, this node is associated with two topic feature words: social network and big data, and each appears once, because t 0 = (social network), t 1 = (big data), then there is f 04 = 1, f 14 =1, the number of user nodes in...
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The invention provides a subject community mining method for an online social networking service.The subject community mining method is based on nonnegative matrix factorization (NMF).User node link information and content information can be integrated in a unified mode through an NMF model, an affiliation matrix between user nodes and communities and a correlation intension matrix between communities and subject feature words are obtained with the matrix approximative decomposition method, and then subject community mining can be directly conducted by means of matrix decomposition information.By the adoption of the method, user node link information and content information can be processed with a unified model, mining is easier and more efficient, mining quality is higher, and therefore the method is more suitable for being actually applied to mining of subject communities in the online social networking service.
Description
technical field [0001] The present invention relates to the technical field of online social network services, and more specifically, relates to a topic community mining method for online social networks. Background technique [0002] The topic community mining of online social networks is different from the traditional community mining based only on the link information of user nodes. It comprehensively considers the links and content information of user nodes, so as to obtain communities with close member node links and similar topic characteristics. The mining results of the topic community have more application value in reality, for example, it can provide strong support for online social network group behavior monitoring, public opinion analysis, e-commerce operators' precise social marketing and advertising placement. [0003] At present, topic community mining has become a new research hotspot in online social network community mining. Researchers have proposed some r...
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IPC IPC(8): G06F17/30G06Q50/00
CPCG06F16/313G06Q50/01
Inventor 贺超波汤庸刘海陈国华付志文杨灵张世龙
Owner ZHONGKAI UNIV OF AGRI & ENG