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Adaptation of offline vertical selection predictions in the presence of user feedback (2009)
| Venue: | In SIGIR 2009 |
| Citations: | 20 - 11 self |
BibTeX
@INPROCEEDINGS{Diaz09adaptationof,
author = {Fernando Diaz},
title = {Adaptation of offline vertical selection predictions in the presence of user feedback},
booktitle = {In SIGIR 2009},
year = {2009},
pages = {323--330},
publisher = {ACM}
}
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Abstract
Web search results often integrate content from specialized corpora known as verticals. Given a query, one important aspect of aggregated search is the selection of relevant verticals from a set of candidate verticals. One drawback to previous approaches to vertical selection is that methods have not explicitly modeled user feedback. However, production search systems often record a variety of feedback information. In this paper, we present algorithms for vertical selection which adapt to user feedback. We evaluate algorithms using a novel simulator which models performance of a vertical selector situated in realistic query traffic.
Keyphrases
user feedback offline vertical selection prediction vertical selection feedback information relevant vertical candidate vertical model performance specialized corpus web search result novel simulator realistic query traffic aggregated search important aspect vertical selector previous approach production search system
