Abstract
As opposed to query modelling, relevance generating interactive query refinement (QR) is a technique aimed at exploiting syntax variations of gradually extended, being removed or replaced with some other keywords query, which depending on the factors like e.g. the information resource, the database structure, or the keyword alignment, facilitates significantly the searching process. Therefore our motivation is to explore the dynamism of the precision trend depended upon the factors analyzed. For a couple of language pairs which constitute multilingual settings, we develop a user-centred framework that imposes distributed search optimization. Our data set contains variety of query types submitted to some translingual distributed search systems that perform a number of syntax-based indexing. We construct a dynamism of precision elevation trend that indicates what factors intensify the relevance set of the system responses from a perspective of the user’s information need.
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Text Retrieval (TREC) conference series http://trec.nist.gov/.
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Mizera-Pietraszko, J., Zgrzywa, A. (2017). Interactive Gradually Generating Relevance Query Refinement Under the Human-Mediated Scenario in Multilingual Settings. In: Zgrzywa, A., Choroś, K., Siemiński, A. (eds) Multimedia and Network Information Systems. Advances in Intelligent Systems and Computing, vol 506. Springer, Cham. https://doi.org/10.1007/978-3-319-43982-2_23
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DOI: https://doi.org/10.1007/978-3-319-43982-2_23
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