Interactive path reasoning on graph for conversational recommendation

W Lei, G Zhang, X He, Y Miao, X Wang… - Proceedings of the 26th …, 2020‏ - dl.acm.org
Traditional recommendation systems estimate user preference on items from past interaction
history, thus suffering from the limitations of obtaining fine-grained and dynamic user …

Open-retrieval conversational question answering

C Qu, L Yang, C Chen, M Qiu, WB Croft… - Proceedings of the 43rd …, 2020‏ - dl.acm.org
Conversational search is one of the ultimate goals of information retrieval. Recent research
approaches conversational search by simplified settings of response ranking and …

Adapting user preference to online feedback in multi-round conversational recommendation

K Xu, J Yang, J Xu, S Gao, J Guo, JR Wen - Proceedings of the 14th …, 2021‏ - dl.acm.org
This paper concerns user preference estimation in multi-round conversational recommender
systems (CRS), which interacts with users by asking questions about attributes and …

Evaluating conversational recommender systems via user simulation

S Zhang, K Balog - Proceedings of the 26th acm sigkdd international …, 2020‏ - dl.acm.org
Conversational information access is an emerging research area. Currently, human
evaluation is used for end-to-end system evaluation, which is both very time and resource …

Learning to ask appropriate questions in conversational recommendation

X Ren, H Yin, T Chen, H Wang, Z Huang… - Proceedings of the 44th …, 2021‏ - dl.acm.org
Conversational recommender systems (CRSs) have revolutionized the conventional
recommendation paradigm by embracing dialogue agents to dynamically capture the fine …

[PDF][PDF] Towards explainable conversational recommendation

Z Chen, X Wang, X **e, M Parsana, A Soni, X Ao… - Proceedings of the …, 2021‏ - ijcai.org
Recent studies have shown that both accuracy and explainability are important for
recommendation. In this paper, we introduce explainable conversational recommendation …

Relevance Feedback with Brain Signals

Z Ye, X **e, Q Ai, Y Liu, Z Wang, W Su… - ACM Transactions on …, 2024‏ - dl.acm.org
The Relevance Feedback (RF) process relies on accurate and real-time relevance
estimation of feedback documents to improve retrieval performance. Since collecting explicit …

Lending interaction wings to recommender systems with conversational agents

J **, X Chen, F Ye, M Yang, Y Feng… - Advances in …, 2024‏ - proceedings.neurips.cc
An intelligent conversational agent (aka, chat-bot) could embrace conversational
technologies to obtain user preferences online, to overcome inherent limitations of …

Learning to infer user implicit preference in conversational recommendation

C Hu, S Huang, Y Zhang, Y Liu - … of the 45th International ACM SIGIR …, 2022‏ - dl.acm.org
Conversational recommender systems (CRS) enable traditional recommender systems to
interact with users by asking questions about attributes and recommending items. The …

Engineering conversational search systems: A review of applications, architectures, and functional components

P Schneider, W Poelman, M Rovatsos… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Conversational search systems enable information retrieval via natural language
interactions, with the goal of maximizing users' information gain over multiple dialogue turns …