Abstract
Query Expansion could bring very significant improvement of baseline results of Information Retrieval process. This has been known for many years, but very detailed results on annotated sets provide richer insight on the preferred added word space. In this work we introduce novel expanded term adequacy measures related to term frequency and inverse document frequency in relevant and non-relevant groups of documents. Term evaluation scores are derived using two term characteristics: inverse term representativeness and term usability. We generate the Optimal Queries based on the documents contents and the Qrels files of data used in the Text Retrieval Conference 2016 – Clinical Decision Support track (TREC-CDS 2016). The improvement can be up to a factor of 2 depending on the evaluation measure. Potentially, the method can be improved by increasing the learning set and applied to retrieval of documents in biomedical contests.
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Acknowledgments
We acknowledge the Poznan University of Technology grant (04/45/DSPB/0185).
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Dutkiewicz, J., Jędrzejek, C. (2019). Calculating Optimal Queries from the Query Relevance File. In: Choroś, K., Kopel, M., Kukla, E., Siemiński, A. (eds) Multimedia and Network Information Systems. MISSI 2018. Advances in Intelligent Systems and Computing, vol 833. Springer, Cham. https://doi.org/10.1007/978-3-319-98678-4_26
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DOI: https://doi.org/10.1007/978-3-319-98678-4_26
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