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Simulating Simple and Fallible Relevance Feedback

机译:模拟简单易失的相关反馈

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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.
机译:相关性反馈(RF)的许多研究都是在实验室条件下使用测试集,测试人员或简单的模拟进行的。这些研究给出了不同的结果。本研究的设计是独特的。首先,最初的查询实际上是由实际最终用户生成的简短查询。其次,我们在几种射频情况下执行用户仿真。第三,我们在提供RF时模拟人为失误,即反馈的不正确性。第四,我们在检索结果的评估中采用分级的相关性评估。研究的问题是:当初始查询短而反馈容易出错时,RF如何影响IR性能?我们的发现表明,非常容易犯错的反馈与伪相关反馈(PRF)并无不同,并且对简短的初始查询无效。但是,凭经验观察到的RF易错性与正确的RF一样有效,并且能够提高简短初始查询的性能。

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