@inproceedings{schneider-etal-2024-engineering,
title = "Engineering Conversational Search Systems: A Review of Applications, Architectures, and Functional Components",
author = "Schneider, Phillip and
Poelman, Wessel and
Rovatsos, Michael and
Matthes, Florian",
editor = "Nouri, Elnaz and
Rastogi, Abhinav and
Spithourakis, Georgios and
Liu, Bing and
Chen, Yun-Nung and
Li, Yu and
Albalak, Alon and
Wakaki, Hiromi and
Papangelis, Alexandros",
booktitle = "Proceedings of the 6th Workshop on NLP for Conversational AI (NLP4ConvAI 2024)",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.nlp4convai-1.5",
pages = "73--88",
abstract = "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.",
}
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<abstract>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.</abstract>
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%0 Conference Proceedings
%T Engineering Conversational Search Systems: A Review of Applications, Architectures, and Functional Components
%A Schneider, Phillip
%A Poelman, Wessel
%A Rovatsos, Michael
%A Matthes, Florian
%Y Nouri, Elnaz
%Y Rastogi, Abhinav
%Y Spithourakis, Georgios
%Y Liu, Bing
%Y Chen, Yun-Nung
%Y Li, Yu
%Y Albalak, Alon
%Y Wakaki, Hiromi
%Y Papangelis, Alexandros
%S Proceedings of the 6th Workshop on NLP for Conversational AI (NLP4ConvAI 2024)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F schneider-etal-2024-engineering
%X 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.
%U https://aclanthology.org/2024.nlp4convai-1.5
%P 73-88
Markdown (Informal)
[Engineering Conversational Search Systems: A Review of Applications, Architectures, and Functional Components](https://aclanthology.org/2024.nlp4convai-1.5) (Schneider et al., NLP4ConvAI-WS 2024)
ACL