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Automated dictionary discovery for the online marketplace

Published: 07 February 2012 Publication History
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  • 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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