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Automated dictionary discovery for the online marketplace

Published: 07 February 2012 Publication History

Abstract

Shopping online has become a prolific activity as the number of online vendors and consumers continue to rise each year. In 2009, almost $15 billion in goods and services were ordered online by Canadians [1]. About 53% of these consumers 'window shop' by doing product research before actually making a purchase. Therefore, it is important that online vendors provide up-to-date and accurate product information to assist users in making educated decisions. In this poster, we present a tool that discovers product features, which will assist vendors and consumers to more accurately compare products in the online marketplace

References

[1]
Statistics Canada Report: www.statcan.gc.ca/dailyquotidien/100927/dq100927a-eng.htm.
[2]
V. Borkar, K. Deshmukh, and S. Sarawagi. Automatic segmentation of text into structured records. SIGMOD Rec., 30(2), 2001.
[3]
S. Godbole, I. Bhattacharya, A. Gupta, and A. Verma. Building re-usable dictionary repositories for real-world text mining. In CIKM, pages 1189--1198, 2010.
[4]
S. Sarawagi and W. W. Cohen. Semi-markov conditional random fields for information extraction. In NIPS, 2004.
[5]
N. Sarkas, S. Paparizos, and P. Tsaparas. Structured annotations of web queries. In SIGMOD Conference, pages 771--782, 2010.
[6]
B. Tan and F. Peng. Unsupervised query segmentation using generative language models and wikipedia. In WWW, pages 347--356, 2008

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cover image ACM Other conferences
iConference '12: Proceedings of the 2012 iConference
February 2012
667 pages
ISBN:9781450307826
DOI:10.1145/2132176

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 February 2012

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iConference '12
iConference '12: iConference 2012
February 7 - 10, 2012
Ontario, Toronto, Canada

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