Data mining method based on decision tree for implicit user behavior in social network
In order to solve the problem of social network that it is difficult to calculate the association similarity in the process of data mining for implicit user behavior,a data mining method based on decision tree for implicit user behavior in social network was proposed.Social network was regarded as a vector space containing different dimensions,and users′ interest space and interest points on specific dimensions were calculated.After determining the sample attribute set,the test branch was established according to the known behavior data,and the attribute weight of branch subset was calculated.In addition,it was iterated until the data points with the same attributes were mined.Test results show that the as-proposed method can ensure accurate mining in the face of different types of implicit user behavior,and the search for target behavior data is effective and practical.
decision treesocial networkimplicit user behaviorvector spaceset of propertiesdata miningweight valueattribute element
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