@inproceedings{e0d9d6530a554bebae6c942ddf783c3f,
title = "Using online relevance feedback to build effective personalized metasearch engine",
abstract = "Metasearch Engine is popular for facilitating users' queries over multiple search engines and increasing the coverage of the WWW. How to rank the merged results becomes crucial for the success of metasearch engines. Many current metasearch engines have poor precision, for one or more of selected source search engine returns irrelevant results. On the other hand, users with different interests may prefer distinct ranking order even for the same query. In this work, we try to use online relevance feedback to improve precision of the search results. At the same time, Users' preferences are recorded during the process of feedback for future ranking. Our elementary experiment shows that it is effective in improving precision of the metasearch engine. {\textcopyright} 2001 IEEE.",
keywords = "Computer science, Corporate acquisitions, Explosives, Feedback, Indexing, Metasearch, Publishing, Search engines, Web sites, World Wide Web",
author = "Shanfeng Zhu and Xiaotie Deng and Kang Chen and Weimin Zheng",
note = "Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to
[email protected].; 2nd International Conference on Web Information Systems Engineering, WISE 2001 ; Conference date: 03-12-2001 Through 06-12-2001",
year = "2001",
doi = "10.1109/WISE.2001.996487",
language = "English",
isbn = "076951393",
volume = "1",
series = "Proceedings of the 2nd International Conference on Web Information Systems Engineering, WISE 2001",
publisher = "IEEE",
pages = "262--268",
booktitle = "Proceedings of the 2nd International Conference on Web Information Systems Engineering, WISE 2001",
address = "United States",
}