TY - GEN
T1 - Engineering Conversational Search Systems
T2 - 6th Workshop on NLP for Conversational AI, NLP4ConvAI 2024
AU - Schneider, Phillip
AU - Poelman, Wessel
AU - Rovatsos, Michael
AU - Matthes, Florian
N1 - Publisher Copyright:
© 2024 Association for Computational Linguistics.
PY - 2024
Y1 - 2024
N2 - Conversational search systems enable information retrieval via natural language interactions, with the goal of maximizing users’ information gain over multiple dialogue turns. The increasing prevalence of conversational interfaces adopting this search paradigm challenges traditional information retrieval approaches, stressing the importance of better understanding the engineering process of developing these systems. We undertook a systematic literature review to investigate the links between theoretical studies and technical implementations of conversational search systems. Our review identifies real-world application scenarios, system architectures, and functional components. We consolidate our results by presenting a layered architecture framework and explaining the core functions of conversational search systems. Furthermore, we reflect on our findings in light of the rapid progress in large language models, discussing their capabilities, limitations, and directions for future research.
AB - Conversational search systems enable information retrieval via natural language interactions, with the goal of maximizing users’ information gain over multiple dialogue turns. The increasing prevalence of conversational interfaces adopting this search paradigm challenges traditional information retrieval approaches, stressing the importance of better understanding the engineering process of developing these systems. We undertook a systematic literature review to investigate the links between theoretical studies and technical implementations of conversational search systems. Our review identifies real-world application scenarios, system architectures, and functional components. We consolidate our results by presenting a layered architecture framework and explaining the core functions of conversational search systems. Furthermore, we reflect on our findings in light of the rapid progress in large language models, discussing their capabilities, limitations, and directions for future research.
UR - http://www.scopus.com/inward/record.url?scp=85204910268&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85204910268
T3 - NLP4ConvAI 2024 - 6th Workshop on NLP for Conversational AI, Proceedings of the Workshop
SP - 73
EP - 88
BT - NLP4ConvAI 2024 - 6th Workshop on NLP for Conversational AI, Proceedings of the Workshop
A2 - Nouri, Elnaz
A2 - Rastogi, Abhinav
A2 - Spithourakis, Georgios
A2 - Liu, Bing
A2 - Chen, Yun-Nung
A2 - Li, Yu
A2 - Albalak, Alon
A2 - Wakaki, Hiromi
A2 - Papangelis, Alexandros
PB - Association for Computational Linguistics (ACL)
Y2 - 16 August 2024
ER -