Mining User Dwell Time for Personalized Web Search Re-Ranking
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 2367-2371.
Abstract
We propose a personalized re-ranking algorithm through mining user dwell times derived from a user's previously online reading or browsing activities. We acquire document level user dwell times via a customized web browser, from which we then infer concept word level user dwell times in order to understand a user's personal interest. According to the estimated concept word level user dwell times, our algorithm can estimate a user's potential dwell time over a new document, based on which personalized webpage re-ranking can be carried out. We compare the rankings produced by our algorithm with rankings generated by popular commercial search engines and a recently proposed personalized ranking algorithm. The results clearly show the superiority of our method.
@inproceedings{ijcai2011p394,
title = {Mining User Dwell Time for Personalized Web Search Re-Ranking},
author = {Xu, Songhua and Jiang, Hao and Lau, Francis Chi-Moon},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-11}},
publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
editor = {Toby Walsh},
pages = {2367--2371},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-394},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-394},
}
TY - CPAPER TI - Mining User Dwell Time for Personalized Web Search Re-Ranking AU - Xu, Songhua AU - Jiang, Hao AU - Lau, Francis Chi-Moon T2 - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11 PB - AAAI Press/International Joint Conferences on Artificial Intelligence PY - 2011 SP - 2367 EP - 2371 DO - 10.5591/978-1-57735-516-8/IJCAI11-394 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-394 ER -Copied
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