Authoritative sources in a hyperlinked environment
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Extracting key terms from noisy and multitheme documents
Proceedings of the 18th international conference on World wide web
Keeping keywords fresh: a BM25 variation for personalized keyword extraction
Proceedings of the 2nd Temporal Web Analytics Workshop
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This paper proposes a method that can extract user interests from the user's Web browsing history. Our method allows easy access to multiple content domains such as blogs, movies, QA sites, etc. since the user does not need to input a separate search query in each domain/site. To extract user interests, the method first extracts candidate keyphrases from the user's web browsed documents. Second, important keyphrases obtained from a link structure analysis of Wikipedia content is extracted from the main contents of web documents. This technique is based on the idea that important keyphrases in Wikipedia are important keyphrases in the real world. Finally, keyphrases contained in the documents important to the user are set in order as user interests. An experiment shows that our method offers improvements over a conventional method and can recommend interests attractive to the user.