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      Improving Retrieval Results with discipline-specific Query Expansion

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          Abstract

          Choosing the right terms to describe an information need is becoming more difficult as the amount of available information increases. Search-Term-Recommendation (STR) systems can help to overcome these problems. This paper evaluates the benefits that may be gained from the use of STRs in Query Expansion (QE). We create 17 STRs, 16 based on specific disciplines and one giving general recommendations, and compare the retrieval performance of these STRs. The main findings are: (1) QE with specific STRs leads to significantly better results than QE with a general STR, (2) QE with specific STRs selected by a heuristic mechanism of topic classification leads to better results than the general STR, however (3) selecting the best matching specific STR in an automatic way is a major challenge of this process.

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          Author and article information

          Journal
          11 June 2012
          Article
          10.1007/978-3-642-33290-6_44
          1206.2126
          e4d4c3a5-d54f-46cc-808a-dc3dc3d4e943

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          6 pages; to be published in Proceedings of Theory and Practice of Digital Libraries 2012 (TPDL 2012)
          cs.IR cs.DL

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