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Promoting Understandability in Consumer Health Information Search

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Advances in Information Retrieval (ECIR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10193))

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Abstract

Search engines have become a common way of obtaining health information. Although access mechanism for factual health information search has developed greatly, complex health searches which do not have a single definitive answer still remain indefinable. Answers to a complex health query contain different viewpoints and confuse a non-expert consumer. It is demanding for a consumer with limited medical knowledge background to get a balanced view of the diverse perspectives. This research proposal points out that what consumers need is comprehensive and useful information. To aid consumers get an improved understanding of the retrieved contents, the proposed approach is adding additional information to the retrieved contents. One applicable way is classifying the retrieved contents as support, neutral or oppose. The classification labels serve as the extra information to supplement the retrieved contents. Other potential extra information and ways to incorporate the information into a search engine are to be researched into in our later work. In this proposal, the challenges are narrated and related work are reviewed. Research questions and overall goals are stated. The proposed work is discussed and research outline is depicted.

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Notes

  1. 1.

    https://www.nlm.nih.gov/mesh/.

  2. 2.

    https://www.nlm.nih.gov/research/umls/.

References

  • Chen, M.W.: Comparison of natural language processing algorithms for medical texts. Ph.D. thesis, Massachusetts Institute of Technology (2015)

    Google Scholar 

  • Donato, D., Bonchi, F., Chi, T., Maarek, Y.: Identifying research missions in yahoo! search pad. In: Proceedings of the 19th International Conference on World wide web, pp. 321–330. ACM (2010)

    Google Scholar 

  • Fox, S., Duggan, M.: Health online 2013. Washington, DC: Pew Internet Am. Life Proj. (2013)

    Google Scholar 

  • Goeuriot, L., Jones, G.J., Kelly, L., Müller, H., Zobel, J.: Medical information retrieval: introduction to the special issue. Inf. Retr. J. 1(19), 1–5 (2016)

    Article  Google Scholar 

  • Liu, T.-Y.: Learning to rank for information retrieval. Found. Trends Inf. Retr. 3(3), 225–331 (2009)

    Article  Google Scholar 

  • Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space (2013). arXiv preprint arXiv:1301.3781

  • Palotti, J., Zuccon, G., Goeuriot, L., Kelly, L., Hanbury, A., Jones, G., Lupu, M., Pecina, P.: Retrieving information about medical symptoms. In: Proceedings of CLEF (2015)

    Google Scholar 

  • Paparrizos, J., White, R.W., Horvitz, E.: Detecting devastating diseases in search logs. In: Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2016)

    Google Scholar 

  • Paul, M.J., White, R.W., Horvitz, E.: Web search as decision support for cancer. In: Proceedings of the 24th International Conference on World Wide Web, pp. 831–841. ACM (2015)

    Google Scholar 

  • Schoenherr, G.P., White, R.W.:Interactions between health searchers and search engines. In: Proceedings of the 37th International ACM SIGIR Conference on Research and development in Information Retrieval, pp. 143–152. ACM (2014)

    Google Scholar 

  • Shen, W., Nie, J.-Y.: Is concept mapping useful for biomedical information retrieval? In: Mothe, J., Savoy, J., Kamps, J., Pinel-Sauvagnat, K., Jones, G.J.F., SanJuan, E., Cappellato, L., Ferro, N. (eds.) CLEF 2015. LNCS, vol. 9283, pp. 281–286. Springer, Heidelberg (2015). doi:10.1007/978-3-319-24027-5_29

    Chapter  Google Scholar 

  • Voorhees, E.M., Hersh, W.R.: Overview of the TREC 2012 medical records track. In: TREC (2012)

    Google Scholar 

  • Wang, C., Cao, L., Zhou, B.: Medical synonym extraction with concept space models (2015). arXiv preprint arXiv:1506.00528

  • White, R.W., Drucker, S.M.: Investigating behavioral variability in web search. In: Proceedings of the 16th International Conference on World Wide Web, pp. 21–30. ACM (2007)

    Google Scholar 

  • Yilmaz, E., Verma, M., Craswell, N., Radlinski, F., Bailey, P.: An analysis of document utility. In: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, pp. 91–100. ACM (2014)

    Google Scholar 

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Correspondence to Hua Yang .

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Yang, H., Goncalves, T. (2017). Promoting Understandability in Consumer Health Information Search. In: Jose, J., et al. Advances in Information Retrieval. ECIR 2017. Lecture Notes in Computer Science(), vol 10193. Springer, Cham. https://doi.org/10.1007/978-3-319-56608-5_72

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  • DOI: https://doi.org/10.1007/978-3-319-56608-5_72

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56607-8

  • Online ISBN: 978-3-319-56608-5

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