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The discovery of user related rare sequential patterns of topics in the Internet document stream
Hu, Zhongyi (1); Wang, Hongan (1); Zhu, Jiaqi (1)
2014
会议名称29th Annual ACM Symposium on Applied Computing, SAC 2014
页码137-138
会议日期March 24, 2014 - March 28, 2014
会议地点Gyeongju, Korea, Republic of
收录类别EI
出版地Association for Computing Machinery
ISBN9781450324694
部门归属(1) Beijing Key Lab. of Human-Computer Interaction, Institute of Software, Chinese Academy of Sciences, China
摘要On the Internet, plain text documents created and viewed by users constitute ever changing document streams. Lots of the literature is devoted to topic modeling, while the sequential patterns of topics in document streams are ignored. In this paper, we deal with the problem of mining user related rare sequential patterns of topics in the Internet document streams, which can be used in many fields, such as real-time user behavioral monitoring on the Internet. We propose an approach to discover rare patterns based on the temporal and probabilistic information of topics. Experiments show that the proposed approach can discover user related rare patterns of topic effectively. Copyright 2014 ACM.; On the Internet, plain text documents created and viewed by users constitute ever changing document streams. Lots of the literature is devoted to topic modeling, while the sequential patterns of topics in document streams are ignored. In this paper, we deal with the problem of mining user related rare sequential patterns of topics in the Internet document streams, which can be used in many fields, such as real-time user behavioral monitoring on the Internet. We propose an approach to discover rare patterns based on the temporal and probabilistic information of topics. Experiments show that the proposed approach can discover user related rare patterns of topic effectively. Copyright 2014 ACM.
语种英语
内容类型会议论文
URI标识http://ir.iscas.ac.cn/handle/311060/16574
专题中国科学院软件研究所
推荐引用方式
GB/T 7714
Hu, Zhongyi ,Wang, Hongan ,Zhu, Jiaqi . The discovery of user related rare sequential patterns of topics in the Internet document stream[C]. Association for Computing Machinery,2014:137-138.
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