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A personalized URL re-ranking methodology using user's browsing behavior
초록
This paper proposes a personalized re-ranking of URLs returned by a search engine using user's browsing behaviors. Our personalization method constructs an index of the anchor text retrieved from the web pages that the user has clicked during his/her past searches. We propose a weight computation method that assigns different values to anchor texts according to user's browsing behaviors such as 'clicking' or 'downloading'. Experiment results show that our method can be practical for saving surfing time and effort to find users' preferred web pages. ? 2008 Springer-Verlag Berlin Heidelberg.
- 제목
- A personalized URL re-ranking methodology using user's browsing behavior
- 저자
- KANG SANGGIL
- 학회명
- Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
- 개최지
- 인천
- 학회 개최일
- 2008-03-26 ~ 2008-03-28