User identification across multiple social networks based on information entropy
Z WU, H YU, S LIU, Y ZHU - Journal of Computer Applications, 2017 - joca.cn
The precision of user identification is low since the subjective weighting algorithms ignore
the special meanings and effects of attributes in applications. To solve this problem, an
Information Entropy based Multiple Social Networks User Identification Algorithm (IE-
MSNUIA) was proposed. Firstly, the data types and physical meanings of different attributes
were analyzed, then different similarity calculation methods were correspondingly adopted.
Secondly, the weights of attributes were determined according to their information entropies …
the special meanings and effects of attributes in applications. To solve this problem, an
Information Entropy based Multiple Social Networks User Identification Algorithm (IE-
MSNUIA) was proposed. Firstly, the data types and physical meanings of different attributes
were analyzed, then different similarity calculation methods were correspondingly adopted.
Secondly, the weights of attributes were determined according to their information entropies …
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