When NLP meets LLM: Neural Approaches to Context-based Conversational Question Answering

— —

Munazza Zaib Quan Z. Sheng (Macquarie University, Australia)

When NLP meets LLM

Neural Approaches to Context-based Conversational Question Answering

Munazza Zaib, Quan Z. Sheng (Macquarie University, Australia), Wei Emma Zhang (The University of Adelaide) , Adnan Mahmood (Macquarie University, Australi)

$143.95 $115.20

Hardback

Not in-store but you can order this
How long will it take?

Availability Information

We source books from suppliers in Australia and overseas. For books we don't currently have in stock, the time it takes to get them from our suppliers can vary widely - from a few days to a few months - so we check each book with each supplier to determine the expected time it will take to be supplied to us.

We then advise you accordingly. If the time taken to get any book is too long for you, you can let us know and we will cancel or adjust your order, and refund as required.

To find out the anticipated arrival time for specific items prior to ordering, please contact us by phone or email:

Phone +61 2 9264 3111, or 1800 4 BOOKS (1800 4 26657) if outside Sydney:
option 1 Abbey's Bookshop (Crime, History, Science, Kids & more) • info@abbeys.com.au
option 2 Language Book Centre (ESL & Foreign Languages) • language@abbeys.com.au
option 3 Galaxy Bookshop (Sci-fi, Fantasy, Romance, Graphic Novels) • sf@galaxybooks.com.au

QTY:

English

CRC Press
15 October 2025

Computational linguistics; Computing: general; Artificial intelligence

This book looks at conversational search in intelligent dialogue systems, as it investigates and addresses the challenges pertinent to effective context incorporation in conversational question answering (ConvQA). The authors explore the possibility of designing a scalable Conversational Question Answering Agent that can handle the challenges of incomplete/ambiguous questions, better able to relate to co-references to cope with the problems of effective weights and optimal threshold selection in vehicular networks. A fundamental emphasis is the understanding of ambiguous follow-up questions and the generation of contextual and question entities to fill in the missing information gaps. Key topics are studied, such as ‘hard history selection’ to filter out the context that is not relevant and performing a re-ranking of the selected turns based on their significance to answer the question as a part of the soft history selection process.

This book aims to demonstrate that the history selection and modelling approaches proposed can effectively improve the performance of ConvQA models in different settings. The proposed models are compared with the state-of-the-art vis-à-vis different conversational datasets and provide new insights into conversational information retrieval. Through a systematic study of structured representations, entity-aware history selection, and open-domain passage retrieval using contrastive learning, this book presents a robust framework for advancing multi-turn QA systems.

It is an essential resource for researchers, practitioners, and graduate students working at the intersection of NLP, dialogue systems, and intelligent information access.

By: Munazza Zaib, Quan Z. Sheng (Macquarie University, Australia), Wei Emma Zhang (The University of Adelaide), Adnan Mahmood (Macquarie University, Australi)
Imprint: CRC Press
Country of Publication: United Kingdom
Dimensions: Height: 216mm, Width: 138mm,
Weight: 350g
ISBN: 9781032970844
ISBN 10: 1032970847
Pages: 102
Publication Date: 15 October 2025
Audience: College/higher education , Professional and scholarly , Primary , Undergraduate
Format: Hardback
Publisher's Status: Active

Munazza Zaib is currently a Postdoctoral Research Fellow at the Department of Human Centred Computing, Faculty of Information Technology, Monash University, Australia. Quan Z. Sheng is a Distinguished Professor and Head of School of Computing at Macquarie University, Australia. ). He is the recipient of the AMiner Most Influential Scholar Award on IoT (2007-2017), ARC (Australian Research Council) Future Fellowship (2014). Wei Emma Zhang is Associate Head of People and Culture at the School of Computer and Mathematical Sciences, and a researcher at the Australian Institute for Machine Learning, the University of Adelaide. Adnan Mahmood is a Lecturer in Computing – IoT and Networking at the School of Computing, Macquarie University, Sydney.