topic modeling for sequences of temporal activities

	topic modeling for sequences of temporal activities
	Shen Zhi-Yong ; Luo Ping ; Xiong Yuhong ; Sun Jun ; Shen Yi-Dong
	2010
会议名称	topic modeling for sequences of temporal activities
会议日期	2010
会议地点	北京
关键词	Computer crime
页码	-
英文摘要	Temporally-ordered activity sequences are popular in many real-world domains. This paper presents an LDA-style topic model for sequences of temporal activities that captures three features of such sequences: 1) the counts of unique activities, 2) the Markov transition dependence and 3) the absolute or relative timestamp on each activity. In modeling the first two features we propose the concept of global transition probability and distinguish it with local transition probability used in previous work. In modeling the third feature, we employ a continuous time distribution to depict the time range of latent topics. The combination of the global transition probability and the temporal information helps to refine the mixture distribution over topics for temporal sequence analysis. We present results on the data of distributed denial-of-service attack and system call traces, qualitatively and quantitatively showing improved topics, better next activity prediction and sequence clustering. ©Copyright The Ninth IEEE International Conference on Data Mining, 2009.
收录类别	EI
会议录	HP Laboratories Technical Report
会议录出版地	United States
内容类型	会议论文
源URL	[http://124.16.136.157/handle/311060/8944]
专题	软件研究所_计算机科学国家重点实验室 _会议论文
推荐引用方式 GB/T 7714	Shen Zhi-Yong,Luo Ping,Xiong Yuhong,et al. topic modeling for sequences of temporal activities[C]. 见:topic modeling for sequences of temporal activities. 北京. 2010.