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The role of knowledge in conceptual retrieval: a study in the domain of clinical medicine

Published: 06 August 2006 Publication History
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  • Abstract

    Despite its intuitive appeal, the hypothesis that retrieval at the level of "concepts" should outperform purely term-based approaches remains unverified empirically. In addition, the use of "knowledge" has not consistently resulted in performance gains. After identifying possible reasons for previous negative results, we present a novel framework for "conceptual retrieval" that articulates the types of knowledge that are important for information seeking. We instantiate this general framework in the domain of clinical medicine based on the principles of evidence-based medicine (EBM). Experiments show that an EBM-based scoring algorithm dramatically outperforms a state-of-the-art baseline that employs only term statistics. Ablation studies further yield a better understanding of the performance contributions of different components. Finally, we discuss how other domains can benefit from knowledge-based approaches.

    References

    [1]
    G. Amati and C. van Rijsbergen. Probabilistic models of information retrieval based on measuring the divergence from randomness. ACM TOIS, 20(4):357--389, 2002.
    [2]
    A. Aronson. Effective mapping of biomedical text to the UMLS Metathesaurus: The MetaMap program. In AMIA 2001.
    [3]
    N. Belkin. Anomalous states of knowledge as a basis for information retrieval. Canadian Journal of Information Science, 5:133--143, 1980.
    [4]
    C. Buckley and D. Harman. Reliable information access final workshop report, 2004.
    [5]
    M. Chambliss and J. Conley. Answering clinical questions. The Journal of Family Practice, 43:140--144, 1996.
    [6]
    J. Chu-Carroll, J. Prager, C. Welty, K. Czuba, and D. Ferrucci. A multi-strategy and multi-source approach to question answering. In TREC 2002.
    [7]
    K. Cogdill and M. Moore. First-year medical students' information needs and resource selection: Responses to a clinical scenario. Bulletin of the Medical Library Association, 85(1):51--54, 1997.
    [8]
    D. Covell, G. Uman, and P. Manning. Information needs in office practice: Are they being met? Annals of Internal Medicine, 103(4):596--599, 1985.
    [9]
    H. Cui, R. Sun, K. Li, M.-Y. Kan, and T.-S. Chua. Question answering passage retrieval using dependency relations. In SIGIR 2005.
    [10]
    S. De Groote and J. Dorsch. Measuring use patterns of online journals and databases. Journal of the Medical Library Association, 91(2):231--241, 2003.
    [11]
    D. Demner-Fushman and J. Lin. Knowledge extraction for clinical question answering: Preliminary results. In Proc. of the AAAI 2005 Workshop on Question Answering in Restricted Domains.
    [12]
    D. Demner-Fushman and J. Lin. Answering clinical questions with knowledge-based and statistical techniques. Computational Linguistics, 2006, in press.
    [13]
    J. Ely, J. Osheroff, M. Ebell, G. Bergus, B. Levy, M. Chambliss, and E. Evans. Analysis of questions asked by family doctors regarding patient care. BMJ, 319:358--361, 1999.
    [14]
    J. Fagan. Experiments in Automatic Phrase Indexing for Document Retrieval: A Comparisons of Syntactic and Non-Syntactic Methods. Ph.D., Cornell, 1987.
    [15]
    L. Freund, E. Toms, and C. Clarke. Modeling task-genre relationships for IR in the Workplace. In SIGIR 2005.
    [16]
    J. Gao, J.-Y. Nie, G. Wu, and G. Cao. Dependence language model for information retrieval In SIGIR 2004.
    [17]
    P. Gorman, J. Ash, and L. Wykoff. Can primary care physicians' questions be answered using the medical journal literature? Bulletin of the Medical Library Association, 82(2):140--146, 1994.
    [18]
    W. Hersh, A. Cohen, J. Yang, R. Bhupatiraju, P. Roberts, and M. Hearst. TREC 2005 genomics track overview. In TREC 2005.
    [19]
    L. Hirschman and R. Gaizauskas. Natural language question answering: The view from here. Natural Language Engineering, 7(4):275--300, 2001.
    [20]
    P. Ingwersen. Cognitive information retrieval. ARIST, 34:3--52, 1999.
    [21]
    N. Kando and M.-K. Leong. Workshop on patent retrieval: SIGIR 2000 workshop report. SIGIR Forum, 34(1):28--30, 2000.
    [22]
    S.-B. Kim, H.-C. Seo, and H.-C. Rim. Information retrieval using word sense: Root sense tagging approach. In SIGIR 2004.
    [23]
    D. Lenat. CYC: A large-scale investment in knowledge infrastructure. CACM, 38(11):33--38, 1995.
    [24]
    D. Lindberg, B. Humphreys, and A. McCray. The Unified Medical Language System. Methods of Information in Medicine, 32(4):281--291, 1993.
    [25]
    D. Metzler and W. Croft. A Markov random field model for term dependencies. In SIGIR 2005.
    [26]
    D. Metzler and W. Croft. Combining the language model and inference network approaches to retrieval. Information Processing and Management, 40(5):735--750, 2004.
    [27]
    R. Mihalcea and D. Moldovan. Semantic indexing using WordNet senses. In Proc. of ACL 2000 Workshop on Recent Advances in NLP and IR.
    [28]
    D. Moldovan, M. Paşca, S. Harabagiu, and M. Surdeanu. Performance issues and error analysis in an open-domain question answering system. In ACL 2002.
    [29]
    S. Narayanan and S. Harabagiu. Question answering based on semantic structures. In COLING 2004.
    [30]
    J. Ponte and W. Croft. A language modeling approach to information retrieval. In SIGIR 1998.
    [31]
    W. Richardson, M. Wilson, J. Nishikawa, and R. Hayward. The well-built clinical question: A key to evidence-based decisions American College of Physicians Journal Club, 123(3):A12--A13, 1995.
    [32]
    T. Rindflesch and M. Fiszman. The interaction of domain knowledge and linguistic structure in natural language processing: Interpreting hypernymic propositions in biomedical text. Journal of Biomedical Informatics, 36(6):462--477, 2003.
    [33]
    S. Robertson, S. Walker, S. Jones, M. Hancock-Beaulieu, and M. Gatford. Okapi at TREC-3. In TREC-3, 1994.
    [34]
    D. Sackett, S. Straus, W. Richardson, W. Rosenberg, and R. Haynes. Evidence-Based Medicine: How to Practice and Teach EBM. Churchill Livingstone, second edition, 2000.
    [35]
    G. Salton. A vector space model for information retrieval. CACM, 18(11):613--620, 1975.
    [36]
    M. Sanderson. Word-sense disambiguation and information retrieval. In SIGIR 1994.
    [37]
    A. Smeaton, R. O'Donnell, and F. Kelledy. Indexing structures derived from syntax in TREC-3: System description. In TREC-3, 1994.
    [38]
    E. Voorhees. Query expansion using lexical-semantic relations. In SIGIR 1994.
    [39]
    E. Voorhees. Using WordNet to disambiguate word senses for text retrieval. In SIGIR 1993.

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      cover image ACM Conferences
      SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
      August 2006
      768 pages
      ISBN:1595933697
      DOI:10.1145/1148170
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 06 August 2006

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      Author Tags

      1. question answering
      2. reranking
      3. semantic models

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      SIGIR06
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      SIGIR06: The 29th Annual International SIGIR Conference
      August 6 - 11, 2006
      Washington, Seattle, USA

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