Data processing method and device

Abstract

The invention discloses a data processing method and device. The method comprises that a first social network model with a first association between representation nodes is obtained; the first socialnetwork model is expressed as a first adjacent matrix according to a preset representation manner; any two nodes directly associated with a first node in the first social network model are recorded asbeing direct associated, and a second adjacent matrix is generated; the structure similarity and the characteristic attribute similarity of the any two nodes with direct association in the second adjacent matrix are obtained; a fusion similarity is determined according to the structure similarity and the characteristic attribute similarity, the determined fusion similarity is screened, and a third adjacent matrix is generated on the basis of the screened fusion similarity; and on the basis of the third adjacent matrix, a second social network model of a second association between the representation nodes is generated.

Description

technical field [0001] The invention relates to data processing technology, in particular to a data processing method and equipment. Background technique [0002] With the rise of social networks, more and more user data are generated, and the analysis of user data in social networks has become an increasingly popular topic; users in social networks are connected to each other to form a network, which is expressed in the form of a network graph In the network structure, nodes can be used to represent users in the network graph, and the edges between nodes represent the friendship between users; traditional research topics based on social network models include community discovery, link prediction, and graph representation. [0003] In the prior art, the reconstructed social network model is generated by computing the social network model based on linear average calculation of the structural similarity and the similarity of feature attributes. However, in a real social netwo...

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Problems solved by technology

However, in a real social network, if two users live in different user communities, and the communities themselves have large differences, then even if the characteristic attributes of these two users are very high, it is meaningless for the social network , that is, the strength of the relationship chain between users and the similarity of feature attributes should satisfy a nonlinear relationship; therefore, in the prior art, the reconstructed social Network models have no practical significance for the study of social network models

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