Semantic ranking and result visualization for life sciences publications

Julia Stoyanovich, William Mee, Kenneth A. Ross

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    An ever-increasing amount of data and semantic knowledge in the domain of life sciences is bringing about new data management challenges. In this paper we focus on adding the semantic dimension to literature search, a central task in scientific research. We focus our attention on PubMed, the most significant bibliographic source in life sciences, and explore ways to use high-quality semantic annotations from the MeSH vocabulary to rank search results. We start by developing several families of ranking functions that relate a search query to a document's annotations. We then propose an efficient adaptive ranking mechanism for each of the families. We also describe a two-dimensional Skyline-based visualization that can be used in conjunction with the ranking to further improve the user's interaction with the system, and demonstrate how such Skylines can be computed adaptively and efficiently. Finally, we evaluate the effectiveness of our ranking with a user study.

    Original languageEnglish (US)
    Title of host publication26th IEEE International Conference on Data Engineering, ICDE 2010 - Conference Proceedings
    Pages860-871
    Number of pages12
    DOIs
    StatePublished - 2010
    Event26th IEEE International Conference on Data Engineering, ICDE 2010 - Long Beach, CA, United States
    Duration: Mar 1 2010Mar 6 2010

    Publication series

    NameProceedings - International Conference on Data Engineering
    ISSN (Print)1084-4627

    Other

    Other26th IEEE International Conference on Data Engineering, ICDE 2010
    CountryUnited States
    CityLong Beach, CA
    Period3/1/103/6/10

    ASJC Scopus subject areas

    • Software
    • Signal Processing
    • Information Systems

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