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 post-processed Google outperforms other forms of search engine restricted to the domain of depressive illness on both relevance and quality.
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References
Bin, L., Lun, K.: The retrieval effectiveness of medical information on the web. International Journal of Medical Informatics 62, 155–163 (2001)
Clarke, M., Oxman, A.: Cochrane Reviewers’ handbook 4.1.1. The Cochrane Library, Oxford (2001)
Griffiths, K., Christensen, H.: Quality of web based information on treatment of depression: cross sectional survey. BMJ 321(7275), 1511–1515 (2000)
Griffiths, K., Tang, T., Hawking, D., Christensen, H.: Automated assessment of the quality of depression websites. Journal of Medical Internet Research 7(5) (2005), http://www.jmir.org/2005/5/e59/
Ilic, D., Bessell, T., Silagy, C., Green, S.: Specialized medical search-engines are no better than general search-engines in sourcing consumer information about androgen deficiency. Human Reproduction 18(3), 557–561 (2003)
Järvelin, K., Kekäläinen, J.: IR methods for retrieving highly relevant documents. In: Proc. SIGIR 2000, Athens, Greece, pp. 41–48 (2000)
Jorm, A., Christensen, H., Griffiths, K., Korten, A., Rodgers, B.: Help for depression: What works (and what doesn’t). Centre for Mental Health Research, Canberra, Australia (2001)
Jorm, A., Christensen, H., Griffiths, K., Korten, A., Rodgers, B.: Effectiveness of complementary and self-help treatments for depression. Medical Journal of Australia 176, S84–S96 (2002)
Robertson, S.E., Walker, S., Hancock-Beaulieu, M., Gatford, M.: Okapi at TREC-3. In: Proc. TREC-3, November 1994, pp. 109–126. NIST spec. pub. 500-225 (1994)
Sormunen, E.: A method for measuring wide range performance of Boolean queries in full-text databases. Ph.D thesis, University of Tampere (2000), http://acta.uta.fi/teos.phtml?3786
Tang, T., Craswell, N., Hawking, D., Griffiths, K., Christensen, H.: Quality and relevance of domain-specific search: A case study in mental health. Information Retrieval 9(2), 207–225 (2006), http://es.csiro.au/pubs/tang_domainspec.pdf
Tang, T., Hawking, D., Craswell, N., Griffiths, K.: Focused crawling for both relevance and quality of medical information. In: Proc. CIKM 2005, pp. 147–154 (2005), http://es.csiro.au/pubs/tang_cikm05.pdf
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Tang, T., Hawking, D., Sankaranarayana, R., Griffiths, K.M., Craswell, N. (2009). Quality-Oriented Search for Depression Portals. In: Boughanem, M., Berrut, C., Mothe, J., Soule-Dupuy, C. (eds) Advances in Information Retrieval. ECIR 2009. Lecture Notes in Computer Science, vol 5478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00958-7_60
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DOI: https://doi.org/10.1007/978-3-642-00958-7_60
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