William Chang
ABSTRACT
In online advertising, pervasive in commercial search engines, advertisers typically bid on few terms, and the scarcity of data makes ad matching difficult. Suggesting additional bidterms can significantly improve ad clickability and conversion rates. In this paper, we present a large-scale bidterm suggestion system that models an advertiser's intent and finds new bidterms consistent with that intent. Preliminary experiments show that our system significantly increases the coverage of a state of the art production system used at Yahoo while maintaining comparable precision.
- V. Abhishek and K. Hosanagar. Keyword generation for search engine advertising using semantic similarity between terms. In ICEC, 2007. Google Scholar
Digital Library
- K. Bartz, V. Murthi, and S. Sebastian. Logistic regression and collaborative filtering for sponsored search term recommendation. In Second Workshop on Sponsored Search Auctions, 2006.Google Scholar
- C. Buckley, G. Salton, and A. Singhal. Automatic query expansion using SMART: TREC-3. In Overview of TREC-3, pages 69--80. DIANE Publishing, 1995.Google Scholar
- T. Elsayed, J. Lin, and D. Oard. Pairwise document similarity in large collections with MapReduce. In ACL, 2008.Google ScholarDigital Library
- D. Gleich and L. Zhukov. SVD based term suggestion and ranking system. In ICDM, 2004. Google ScholarDigital Library
- A. Joshi and R. Motwani. Keyword generation for search engine advertising. In ICDM, 2006. Google ScholarDigital Library
- X. Li, Y.-Y. Wang, and A. Acero. Learning query intent from regularized click graphs. In SIGIR, 2008. Google ScholarDigital Library
- V. M. Peter Anick and S. Sebastian. Similar term discovery using web search. In LREC'08, May 2008.Google Scholar
- F. Radlinski, A. Broder, P. Ciccolo, E. Gabrilovich, V. Josifovski, and L. Riedel. Optimizing relevance and revenue in ad search: a query substitution approach. In SIGIR, 2008. Google ScholarDigital Library
- S. Sarawagi and A. Kirpal. Efficient set joins on similarity predicates. In SIGMOD, 2004. Google ScholarDigital Library
Index Terms
- Towards intent-driven bidterm suggestion
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