Journal
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
Volume 24, Issue 5, Pages 854-867Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TKDE.2011.17
Keywords
Evolving fuzzy systems; fuzzy-rule-based (FRB) classifiers; user modeling
Categories
Funding
- Spanish Government [TRA2007-67374-C02-02]
- EPSRC [EP/D077680/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/D077680/1] Funding Source: researchfish
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Knowledge about computer users is very beneficial for assisting them, predicting their future actions or detecting masqueraders. In this paper, a new approach for creating and recognizing automatically the behavior profile of a computer user is presented. In this case, a computer user behavior is represented as the sequence of the commands she/he types during her/his work. This sequence is transformed into a distribution of relevant subsequences of commands in order to find out a profile that defines its behavior. Also, because a user profile is not necessarily fixed but rather it evolves/changes, we propose an evolving method to keep up to date the created profiles using an Evolving Systems approach. In this paper, we combine the evolving classifier with a trie-based user profiling to obtain a powerful self-learning online scheme. We also develop further the recursive formula of the potential of a data point to become a cluster center using cosine distance, which is provided in the Appendix. The novel approach proposed in this paper can be applicable to any problem of dynamic/evolving user behavior modeling where it can be represented as a sequence of actions or events. It has been evaluated on several real data streams.
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