Open-Domain答疑

IF 8.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Foundations and Trends in Information Retrieval Pub Date : 2007-08-01 DOI:10.1561/1500000001
J. Prager
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引用次数: 94

摘要

表现最好的问答(QA)系统有两种类型:一种是年复一年表现良好的、稳定的、完善的、多方面的系统,另一种是采用完全创新的方法而脱颖而出的系统,它的表现几乎超过了其他所有系统。本文将深入研究这两种类型的系统。我们建立了一个“典型的”qa系统,并涵盖了组件模块常用的方法。理解这一点将使任何熟练的系统开发人员能够构建自己的qa系统。幸运的是,开发人员可以免费提供许多组件,使其成为研究生级项目的合理期望。我们还研究了一些表现良好的系统,它们采用了有趣和创新的方法。
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Open-Domain Question-Answering
Open-Domain Question Answering is an introduction to the field of Question Answering (QA). It covers the basic principles of QA along with a selection of systems that have exhibited interesting and significant techniques, so it serves more as a tutorial than as an exhaustive survey of the field. Starting with a brief history of the field, it goes on to describe the architecture of a QA system before analysing in detail some of the specific approaches that have been successfully deployed by academia and industry designing and building such systems. Open-Domain Question Answering is both a guide for beginners who are embarking on research in this area, and a useful reference for established researchers and practitioners in this field.
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来源期刊
Foundations and Trends in Information Retrieval
Foundations and Trends in Information Retrieval COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
39.10
自引率
0.00%
发文量
3
期刊介绍: The surge in research across all domains in the past decade has resulted in a plethora of new publications, causing an exponential growth in published research. Navigating through this extensive literature and staying current has become a time-consuming challenge. While electronic publishing provides instant access to more articles than ever, discerning the essential ones for a comprehensive understanding of any topic remains an issue. To tackle this, Foundations and Trends® in Information Retrieval - FnTIR - addresses the problem by publishing high-quality survey and tutorial monographs in the field. Each issue of Foundations and Trends® in Information Retrieval - FnT IR features a 50-100 page monograph authored by research leaders, covering tutorial subjects, research retrospectives, and survey papers that provide state-of-the-art reviews within the scope of the journal.
期刊最新文献
Multi-hop Question Answering User Simulation for Evaluating Information Access Systems Conversational Information Seeking Perspectives of Neurodiverse Participants in Interactive Information Retrieval Efficient and Effective Tree-based and Neural Learning to Rank
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