research-article

Generating exact- and ranked partially-matched answers to questions in advertisements

Authors:

Yiu-Kai NgAuthors Info & Claims

Proceedings of the VLDB Endowment, Volume 5, Issue 3

Pages 217 - 228

https://doi.org/10.14778/2078331.2078337

Published: 01 November 2011 Publication History

Abstract

Taking advantage of the Web, many advertisements (ads for short) websites, which aspire to increase client's transactions and thus profits, offer searching tools which allow users to (i) post keyword queries to capture their information needs or (ii) invoke form-based interfaces to create queries by selecting search options, such as a price range, filled-in entries, check boxes, or drop-down menus. These search mechanisms, however, are inadequate, since they cannot be used to specify a natural-language query with rich syntactic and semantic content, which can only be handled by a question answering (QA) system. Furthermore, existing ads websites are incapable of evaluating arbitrary Boolean queries or retrieving partially-matched answers that might be of interest to the user whenever a user's search yields only a few or no results at all. In solving these problems, we present a QA system for ads, called CQAds, which (i) allows users to post a natural-language question Q for retrieving relevant ads, if they exist, (ii) identifies ads as answers that partially-match the requested information expressed in Q, if insufficient or no answers to Q can be retrieved, which are ordered using a similarity-ranking approach, and (iii) analyzes incomplete or ambiguous questions to perform the "best guess" in retrieving answers that "best match" the selection criteria specified in Q. CQAds is also equipped with a Boolean model to evaluate Boolean operators that are either explicitly or implicitly specified in Q, i.e., with or without Boolean operators specified by the users, respectively. CQAds is easy to use, scalable to all ads domains, and more powerful than search tools provided by existing ads websites, since its query-processing strategy retrieves relevant ads of higher quality and quantity. We have verified the accuracy of CQAds in retrieving ads on eight ads domains and compared its ranking strategy with other well-known ranking approaches.

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Cited By

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Zhao LDeng TFeng L(2013)ShoppingCat: relocating products from the Web in online shoppingScience China Information Sciences10.1007/s11432-013-4989-056:9(1-13)Online publication date: 10-Sep-2013
https://doi.org/10.1007/s11432-013-4989-0
Deng TZhao LFeng L(2013)Dealing with Context Ambiguity in Context-Based Information Re-findingOn the Move to Meaningful Internet Systems: OTM 2013 Conferences10.1007/978-3-642-41030-7_50(685-702)Online publication date: 2013
https://doi.org/10.1007/978-3-642-41030-7_50

Generating exact- and ranked partially-matched answers to questions in advertisements
1. Information systems

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cover image Proceedings of the VLDB Endowment

Proceedings of the VLDB Endowment Volume 5, Issue 3

November 2011

117 pages

ISSN:2150-8097

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Published: 01 November 2011

Published in PVLDB Volume 5, Issue 3

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Cited By

Pera MNg Y(2013)A group recommender for movies based on content similarity and popularityInformation Processing and Management: an International Journal10.1016/j.ipm.2012.07.00749:3(673-687)Online publication date: 1-May-2013
https://dl.acm.org/doi/10.1016/j.ipm.2012.07.007
Zhao LDeng TFeng L(2013)ShoppingCat: relocating products from the Web in online shoppingScience China Information Sciences10.1007/s11432-013-4989-056:9(1-13)Online publication date: 10-Sep-2013
https://doi.org/10.1007/s11432-013-4989-0
Deng TZhao LFeng L(2013)Dealing with Context Ambiguity in Context-Based Information Re-findingOn the Move to Meaningful Internet Systems: OTM 2013 Conferences10.1007/978-3-642-41030-7_50(685-702)Online publication date: 2013
https://doi.org/10.1007/978-3-642-41030-7_50

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