OA user behavior analysis with the heterogeneous information network model

被引:3
|
作者
Yang, Lin [1 ]
Wang, Yilin [2 ]
Zhou, Yun [2 ]
Wang, Jiang [2 ]
Fan, Changjun [2 ]
Zhu, Cheng [2 ]
机构
[1] Acad Mil Med Sci, Inst Syst Engn, Xianghongqi Rd, Beijing, Peoples R China
[2] Natl Univ Def Technol, Sci & Technol Informat Syst Engn Lab, 109 Deya Rd, Changsha, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
D O I
10.1016/j.physa.2018.09.116
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
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. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:552 / 562
页数:11
相关论文
共 50 条
  • [1] Heterogeneous information network embedding for user behavior analysis on social media
    Zhao, Xiaofang
    Jin, Zhigang
    Liu, Yuhong
    Hu, Yi
    [J]. NEURAL COMPUTING & APPLICATIONS, 2022, 34 (07): : 5683 - 5699
  • [2] Heterogeneous information network embedding for user behavior analysis on social media
    Xiaofang Zhao
    Zhigang Jin
    Yuhong Liu
    Yi Hu
    [J]. Neural Computing and Applications, 2022, 34 : 5683 - 5699
  • [3] Fusing User Reviews Into Heterogeneous Information Network Recommendation Model
    Chen, Xu
    Tian, Jingjing
    Tian, Xinxin
    Liu, Shudong
    [J]. IEEE ACCESS, 2022, 10 : 63672 - 63683
  • [4] User behavior prediction via heterogeneous information preserving network embedding
    Yuan, Weiwei
    He, Kangya
    Han, Guangjie
    Guan, Donghai
    Khattak, Asad Masood
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2019, 92 : 52 - 58
  • [5] Heterogeneous Cellular Network User Distribution Model
    Li, Chao
    Yongacoglu, Abbas
    D'Amours, Claude
    [J]. 2016 8TH IEEE LATIN-AMERICAN CONFERENCE ON COMMUNICATIONS (LATINCOM), 2016,
  • [6] Investment behavior prediction in heterogeneous information network
    Zeng, Xiangxiang
    Li, You
    Leung, Stephen C. H.
    Lin, Ziyu
    Liu, Xiangrong
    [J]. NEUROCOMPUTING, 2016, 217 : 125 - 132
  • [7] User behavior prediction via heterogeneous information in social networks
    Tian, Xiangbo
    Qiu, Liqing
    Zhang, Jianyi
    [J]. INFORMATION SCIENCES, 2021, 581 : 637 - 654
  • [8] Visual Analysis and Interactive Comparison for Heterogeneous Information Network Embedding Model
    Wang, Youyan
    Tang, Ying
    [J]. Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics, 2021, 33 (12): : 1821 - 1829
  • [9] A Survey of Heterogeneous Information Network Analysis
    Shi, Chuan
    Li, Yitong
    Zhang, Jiawei
    Sun, Yizhou
    Yu, Philip S.
    [J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2017, 29 (01) : 17 - 37
  • [10] Predicting User Preferences via Heterogeneous Information Network and Metric Learning
    Li, Xiaotong
    Tang, Yan
    Yuan, Yuan
    Chen, Yingpei
    [J]. KNOWLEDGE SCIENCE, ENGINEERING AND MANAGEMENT, PT I, 2021, 12815 : 656 - 665