Among the many techniques that compose an intelligent Web, a Conversational System (such as Google Now, Apple Siri, and Microsoft Cortana) is one that serves as the direct interactive portal for end-users, which is expected to revolutionize human-computer interaction in the coming years. With recent progress on IR, NLP and IoT, such systems have also been deployed as physical devices such as Google Home, Amazon Alexa, and Apple HomePod, opening up more opportunities for applications in a smart home. Due to users’ constant need to look for information to support both work and daily life, a Conversational Search or Recommendation system will be one of the key techniques. Conversational search and recommendation aim at finding or recommending the most relevant information (e.g., web pages, answers, movies, products) for users based on textual- or spoken-dialogs, through which users can communicate with the system more efficiently using natural language conversations.

 

Related Publications:

[1] Yongfeng Zhang, Xu Chen, Qingyao Ai, Liu Yang, and W. Bruce Croft. Towards Conversational Search and Recommendation: System Ask, User Respond. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM 2018), October 22 – 26, 2018, Turin, Italy.

[2] Liu Yang, Minghui Qiu, Chen Qu, Jiafeng Guo, Yongfeng Zhang, Bruce Croft, Jun Huang, Haiqing Chen. Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems. In Proceedings of the 41th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), July 8 – 12, 2018, Ann Arbor, Michigan, USA.

[3] Chen Qu, Liu Yang, Bruce Croft, Johanne R Trippas, Yongfeng Zhang and Minghui Qiu. Analyzing and Characterizing User Intent in Information-seeking Conversations. In Proceedings of the 41th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), July 8 – 12, 2018, Ann Arbor, Michigan, USA.

[4] Liu Yang, Hamed Zamani, Yongfeng Zhang, Jiafeng Guo, and W. Bruce Croft. Neural Matching Models for Question Retrieval and Next Question Prediction in Conversation. In Proceedings of the SIGIR 2017 Workshop on Neural Information Retrieval (NEUIR 2017), August 7 – 11, 2017, Tokyo, Japan.

[5] Chen Qu, Liu Yang, Bruce Croft, Yongfeng Zhang, Johanne R Trippas and Minghui Qiu. User Intent Prediction in Information-seeking Conversations. In Proceedings of the 2019 ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2019), March 10 – 14, 2019, Glasgow, Scotland, UK.

[6] Chen Qu, Liu Yang, Bruce Croft, Falk Scholer and Yongfeng Zhang. Answer Interaction in Non-factoid Question Answering Systems. In Proceedings of the 2019 ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2019), March 10 – 14, 2019, Glasgow, Scotland, UK.