2024 ACL ACL 2024

Engineering Conversational Search Systems: A Review of Applications, Architectures, and Functional Components

Abstract

AbstractConversational search systems enable information retrieval via natural language interactions, with the goal of maximizing usersโ€™ 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.

๐ŸŒ‰ Interdisciplinary Bridge โ€” Artificial Intelligence and Computer Science and Natural Language Processing
๐Ÿฃ Hot Topic Early Bird โ€” multi-turn dialogue
๐Ÿ Cross-Pollinator โ€” Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio