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2013 IEEE 29th International Conference on Data Engineering (ICDE) (2010)
Long Beach, CA, USA
Mar. 1, 2010 to Mar. 6, 2010
ISBN: 978-1-4244-5445-7
pp: 860-871
Kenneth A. Ross , Columbia University, New York, USA
Julia Stoyanovich , Columbia University, New York, USA
William Mee , Columbia University, New York, USA
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.
Kenneth A. Ross, Julia Stoyanovich, William Mee, "Semantic ranking and result visualization for life sciences publications", 2013 IEEE 29th International Conference on Data Engineering (ICDE), vol. 00, no. , pp. 860-871, 2010, doi:10.1109/ICDE.2010.5447931
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