Constructing a User Preference Ontology for Anti-spam Mail Systems

Authors:
Jongwan Kim;Dejing Dou;Haishan Liu;Donghwi Kwak
Affiliations:
School of Computer and Information Technology, Daegu University, Gyeonsan, Gyeongbuk. 712-714, South Korea;Department of Computer and Information Science, University of Oregon Eugene, Oregon 97403, USA;Department of Computer and Information Science, University of Oregon Eugene, Oregon 97403, USA;Department of Computer and Information Science, University of Oregon Eugene, Oregon 97403, USA
Venue:
CAI '07 Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Year:
2007

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Abstract

The judgment that whether an email is spam or non-spam may vary from person to person. Different individuals can have totally different responses to the same email based on their preferences. This paper presents an innovative approach that incorporates user preferences to construct an anti-spam mail system, which is different from the conventional content-based approaches. We build a user preference ontology to formally represent the important concepts and rules derived from a data mining process. Then we use an inference engine that utilizes the knowledge to predict the user's action on new incoming emails. We also suggest a new rule optimization procedure inspired from logic synthesis to improve comprehensibility and exclude redundant rules. Experimental results showed that our user preference based architecture achieved good performance and the rules derived from the architecture and the optimization method have better quality in terms of comprehensibility.