Mining User Dwell Time for Personalized Web Search Re-Ranking
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.
Cite
Text
Xu et al. "Mining User Dwell Time for Personalized Web Search Re-Ranking." International Joint Conference on Artificial Intelligence, 2011. doi:10.5591/978-1-57735-516-8/IJCAI11-394Markdown
[Xu et al. "Mining User Dwell Time for Personalized Web Search Re-Ranking." International Joint Conference on Artificial Intelligence, 2011.](https://mlanthology.org/ijcai/2011/xu2011ijcai-mining/) doi:10.5591/978-1-57735-516-8/IJCAI11-394BibTeX
@inproceedings{xu2011ijcai-mining,
title = {{Mining User Dwell Time for Personalized Web Search Re-Ranking}},
author = {Xu, Songhua and Jiang, Hao and Lau, Francis Chi-Moon},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2011},
pages = {2367-2372},
doi = {10.5591/978-1-57735-516-8/IJCAI11-394},
url = {https://mlanthology.org/ijcai/2011/xu2011ijcai-mining/}
}