Quality-oriented search for depression portals

Thanh Tang*, David Hawking, Ramesh Sankaranarayana, Kathleen M. Griffiths, Nick Craswell

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    5 Citations (Scopus)

    Abstract

    The problem of low-quality information on the Web is nowhere more important than in the domain of health, where unsound information and misleading advice can have serious consequences. The quality of health web sites can be rated by subject experts against evidence-based guidelines. We previously developed an automated quality rating technique (AQA) for depression websites and showed that it correlated 0.85 with such expert ratings. In this paper, we use AQA to filter or rerank Google results returned in response to queries relating to depression. We compare this to an unrestricted quality-oriented (AQA based) focused crawl starting from an Open Directory category and a conventional crawl with manually constructed seedlist and inclusion rules. The results show that postprocessed Google outperforms other forms of search engine restricted to the domain of depressive illness on both relevance and quality.

    Original languageEnglish
    Title of host publicationAdvances in Information Retrieval - 31th European Conference on IR Research, ECIR 2009, Proceedings
    Pages637-644
    Number of pages8
    DOIs
    Publication statusPublished - 2009
    Event31th European Conference on Information Retrieval, ECIR 2009 - Toulouse, France
    Duration: 6 Apr 20099 Apr 2009

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume5478 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference31th European Conference on Information Retrieval, ECIR 2009
    Country/TerritoryFrance
    CityToulouse
    Period6/04/099/04/09

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