OA user behavior analysis with the heterogeneous information network model

Lin Yang, Yilin Wang, Yun Zhou, Jiang Wang, Changjun Fan and Cheng Zhu

Physica A: Statistical Mechanics and its Applications, 2019, vol. 516, issue C, 552-562

Abstract: Analysis of network users’ behaviors is an important part for improving network security. This paper analyzes users’ group behavior via their interactions within the Office Application (OA) system. Specifically, we construct a heterogeneous information network model based on the interactive messages among users in the OA system. The model contains two types of nodes: user and topic nodes, and relationships between users and topics that are encoded in matrices. We then elicit several meta paths in the model, which integrates both user interaction and semantic information, and propose a community division method for group user behavior analysis. To verify the proposed method, we conduct experiments on five-year data collected from a real OA system. The results evaluated by an improved indicator named Normalized Mutual Information show the effectiveness of our work.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:516:y:2019:i:c:p:552-562

DOI: 10.1016/j.physa.2018.09.116

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