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Supporting BioMedical Information Retrieval: The BioTracer Approach

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Transactions on Large-Scale Data- and Knowledge-Centered Systems IV

Part of the book series: Lecture Notes in Computer Science ((TLDKS,volume 6990))

Abstract

The large amount and diversity of available biomedical information has put a high demand on existing search systems. Such a tool should be able to not only retrieve the sought information, but also filter out irrelevant documents, while giving the relevant ones the highest ranking. Focusing on biomedical information, this work investigates how to improve the ability for a system to find and rank relevant documents. To achieve this goal, we apply a series of information retrieval techniques to search in biomedical information and combine them in an optimal manner. These techniques include extending and using well-established information retrieval (IR) similarity models such as the Vector Space Model (VSM) and BM25 and their underlying scoring schemes. The techniques also allow users to affect the ranking according to their view of relevance. The techniques have been implemented and tested in a proof-of-concept prototype called BioTracer, which extends a Java-based open source search engine library. The results from our experiments using the TREC 2004 Genomic Track collection are promising. Our investigation have also revealed that involving the user in the search process will indeed have positive effects on the ranking of search results, and that the approaches used in BioTracer can be used to meet the user’s information needs.

This article is a revised and an extended version of the ITBAM 2010 paper [1].

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Author information

Authors and Affiliations

  1. Department of Computer and Information Science, Norwegian University of Science and Technology (NTNU), N-7491, Trondheim, Norway

    Heri Ramampiaro

  2. Dept. of Computer Science, University of California, Irvine (UCI), Irvine, CA, 92697-3425, USA

    Chen Li

Authors
  1. Heri Ramampiaro
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  2. Chen Li
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Editor information

Editors and Affiliations

  1. Institut de Recherche en Informatique de Toulouse (IRIT), Paul Sabatier University, 118, route de Narbonne, 31062, Toulouse Cedex, France

    Abdelkader Hameurlain

  2. University of Linz, FAW, Altenbergerstraße 69, 4040, Linz, Austria

    Josef Küng  & Roland Wagner  & 

  3. Department of Computer Science, Ludwig-Maximilians-Universität, Oettingenstrasse 67, 80538, München, Germany

    Christian Böhm

  4. Institut für Informatik-Systeme, Alpen Adria Universität Klagenfurt, Universitätsstr. 65, 9020, Klagenfurt, Austria

    Johann Eder

  5. Department of Scientific Computing, Florida State University, 400 Dirac Science Library, 32306-4120, Tallahassee, FL, USA

    Claudia Plant

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Ramampiaro, H., Li, C. (2011). Supporting BioMedical Information Retrieval: The BioTracer Approach. In: Hameurlain, A., Küng, J., Wagner, R., Böhm, C., Eder, J., Plant, C. (eds) Transactions on Large-Scale Data- and Knowledge-Centered Systems IV. Lecture Notes in Computer Science, vol 6990. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23740-9_4

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  • DOI: https://doi.org/10.1007/978-3-642-23740-9_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23739-3

  • Online ISBN: 978-3-642-23740-9

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