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| topic modeling for sequences of temporal activities | |
| Shen Zhi-Yong; Luo Ping; Xiong Yuhong; Sun Jun; Shen Yi-Dong | |
| 2010 | |
| Conference Name | topic modeling for sequences of temporal activities |
| Source | HP Laboratories Technical Report |
| Pages | - |
| Conference Date | 2010 |
| Conference Place | 北京 |
| Indexed Type | EI |
| Publish Place | United States |
| Department | (1) Institute of Software, CAS, China; (2) Graduate University of Chinese Academy of Sciences, China; (3) Hewlett Packard Labs China, China |
| English Abstract | 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. |
| Keyword | Computer Crime |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/8944 |
| Collection | 基础软件与系统重点实验室 |
| Recommended Citation GB/T 7714 | Shen Zhi-Yong,Luo Ping,Xiong Yuhong,et al. topic modeling for sequences of temporal activities[C]. United States,2010:-. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| HPL-2010-160.pdf（321KB） | 开放获取 | -- | Application Full Text | |||
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