Simulating simple and fallible relevance feedback

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Abstract

Much of the research in relevance feedback (RF) has been performed under laboratory conditions using test collections and either test persons or simple simulation. These studies have given mixed results. The design of the present study is unique. First, the initial queries are realistically short queries generated by real end-users. Second, we perform a user simulation with several RF scenarios. Third, we simulate human fallibility in providing RF, i.e., incorrectness in feedback. Fourth, we employ graded relevance assessments in the evaluation of the retrieval results. The research question is: how does RF affect IR performance when initial queries are short and feedback is fallible? Our findings indicate that very fallible feedback is no different from pseudo-relevance feedback (PRF) and not effective on short initial queries. However, RF with empirically observed fallibility is as effective as correct RF and able to improve the performance of short initial queries.

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Baskaya, F., Keskustalo, H., & Järvelin, K. (2011). Simulating simple and fallible relevance feedback. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6611 LNCS, pp. 593–604). Springer Verlag. https://doi.org/10.1007/978-3-642-20161-5_59

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