Automatically sharing web experiences through a hyperdocument recommender system

Angelov

IEEE Trans. Knowl. Data Eng.

et al. 2012

114

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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Section: Background and Related Workmentioning

confidence: 99%

Creating Evolving User Behavior Profiles Automatically

Angelov

IEEE Trans. Knowl. Data Eng.

et al. 2012

114

show abstract

“…In addition, to find out relevant information under the human behavior, many methods have been used: Macedo et al [7] propose a system (WebMemex) that provides recommended information based on the captured history of navigation from a list of known users. Gody and Amandi [8] present a technique to generate readable user profiles that accurately capture interests by observing their behavior on the Web.…”

Section: Background and Related Workmentioning

confidence: 99%

Evolving systems for computer user behavior classification

2013 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS)

Sanchís

2013

“…To model, recognize, or classify the behavior of a computer user is very useful in many different computer areas: Discovery of navigation patterns [9], Web recommender systems [10] or Computer security [11]. For this reason, the literature of agent modeling is truly vast.…”

Section: Background and Related Workmentioning

confidence: 99%

User modeling: Through statistical analysis and an evolving classifier

Angelov

International Conference on Fuzzy Systems

et al. 2010