Finding User Semantics on the Web using Word Co-occurrence Information

With the currently growing interest in the Semantic Web, describing user semantics to model users and their social relationships is coming to play an important role. This paper proposes a novel keyword extraction method to extract user semantics from the Web. Based on co-occurrence information of words, the proposed method extracts relevant keywords depending on the context of a person. Our evaluation shows better performance to tfidf -based keyword extraction. We also discuss application of our method in the Semantic Web.