ICTIR教程:现代查询性能预测:理论与实践

Haggai Roitman
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引用次数: 7

摘要

查询性能预测(Query performance prediction, QPP)是一项核心的信息检索(information retrieval, IR)任务,其主要目标是在缺乏相关性判断的情况下评估检索质量。QPP的应用非常广泛,包括自动查询重构、融合和排名选择、分布式搜索和内容分析等。本教程的主要目的是介绍QPP在IR中的子研究领域的最新进展,包括理论和应用。在理论方面,我们将介绍现代QPP框架,这些框架促进了我们对核心QPP任务的理解。在应用方面,本教程将建立QPP理论及其在各种现代红外应用中的应用之间的联系,讨论其优缺点,局限性,挑战和开放的研究问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ICTIR Tutorial: Modern Query Performance Prediction: Theory and Practice
Query performance prediction (QPP) is a core information retrieval (IR) task whose primary goal is to assess retrieval quality in the absence of relevance judgments. Applications of QPP are numerous, and include, among others, automatic query reformulation, fusion and ranker selection, distributed search and content analysis. The main objective of this tutorial is to introduce recent advances in the sub-research area of QPP in IR, covering both theory and applications. On the theoretical side, we will introduce modern QPP frameworks, which have advanced our understanding of the core QPP task. On the application side, the tutorial will set the connection between QPP theory and its usage in various modern IR applications, discussing the pros and cons, limitations, challenges and open research questions.
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