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Titlebook: Neural Approaches to Conversational Information Retrieval; Jianfeng Gao,Chenyan Xiong,Nick Craswell Book 2023 The Editor(s) (if applicable

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書目名稱Neural Approaches to Conversational Information Retrieval
編輯Jianfeng Gao,Chenyan Xiong,Nick Craswell
視頻videohttp://file.papertrans.cn/664/663529/663529.mp4
概述Surveys recent advances in CIR with an emphasis on recently developed neural approaches.Provides a broad overview of algorithms and methods for developing the main CIR modules.Overview of research pla
叢書名稱The Information Retrieval Series
圖書封面Titlebook: Neural Approaches to Conversational Information Retrieval;  Jianfeng Gao,Chenyan Xiong,Nick Craswell Book 2023 The Editor(s) (if applicable
描述.This book surveys recent advances in Conversational Information Retrieval (CIR), focusing on neural approaches that have been developed in the last few years. Progress in deep learning has brought tremendous improvements in natural language processing (NLP) and conversational AI, leading to a plethora of commercial conversational services that allow naturally spoken and typed interaction, increasing the need for more human-centric interactions in IR..The book contains nine chapters. Chapter 1 motivates the research of CIR by reviewing the studies on how people search and subsequently defines a CIR system and a reference architecture which is described in detail in the rest of the book. Chapter 2 provides a detailed discussion of techniques for evaluating a CIR system – a goal-oriented conversational AI system with a human in the loop. Then Chapters 3 to 7 describe the algorithms and methods for developing the main CIR modules (or sub-systems). In Chapter 3, conversational document search is discussed, which can be viewed as a sub-system of the CIR system. Chapter 4 is about algorithms and methods for query-focused multi-document summarization. Chapter 5 describes various neural mo
出版日期Book 2023
關(guān)鍵詞Information Retrieval; Neural Networks; Deep Learning; Question Answering; Chatbots; Knowledge Graphs; Hum
版次1
doihttps://doi.org/10.1007/978-3-031-23080-6
isbn_softcover978-3-031-23082-0
isbn_ebook978-3-031-23080-6Series ISSN 1871-7500 Series E-ISSN 2730-6836
issn_series 1871-7500
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Conversational Machine Comprehension,This chapter discusses neural approaches to conversational machine comprehension (CMC). A CMC module, which is often referred to as reader, generates a direct answer to a user query based on query-relevant documents retrieved by the document search module.
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Conclusions and Research Trends,We conclude the book with a brief discussion of research trends and areas for future work.
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Case Study of Commercial Systems, our review to summarizing published material about the systems. We first present an overview of research platforms and toolkits which enable scientists and practitioners to build conversational experiences. Then we conclude by reviewing historical highlights and recent trends in a variety of application areas.
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