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Fusion of Knowledge-intensive and Statistical Approaches for Retrieving and Annotating Textual Genomics Documents

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Aronson AR, Demner-Fushman D, Humphrey SM, Lin J, Liu H, Ruch P, Ruiz ME, Smith LH, Tanabe LK, Wilbur WJ
Proc TREC 2005, 36-45
Abstract: 

This paper represents a continuation of research into the retrieval and annotation of textual genomics documents (bothMEDLINE citations and full text articles) for the purpose of satisfying biologists' real information needs. The overallapproach taken here for both the ad hoc retrieval and categorization tasks within the TREC genomics track in 2005 was onecombining the results of several NLP, statistical and ML methods, using a fusion method for ad hoc retrieval and ensemblemethods for categorization. The results show that fusion approaches can improve the final outcome for the ad hoc and thecategorization tasks, but that care must be taken in order to take advantage of the strengths of the constituent methods.

Aronson AR, Demner-Fushman D, Humphrey SM, Lin J, Liu H, Ruch P, Ruiz ME, Smith LH, Tanabe LK, Wilbur WJ. Fusion of Knowledge-intensive and Statistical Approaches for Retrieving and Annotating Textual Genomics Documents Proc TREC 2005, 36-45