ABSTRACT
The workshop on Supporting and Understanding of (multi-party) conversational Dialogues (SUD) seeks to encourage researchers to investigate automated methods to analyze and understand conversations, and also explore methodologies for proactively providing assistance to the communicating parties during conversations, ranging from summarizing the minutes of meetings to automatically keeping track of action items etc. The workshop will have (1) a regular research paper track, and a more focused (2) data challenge track, inviting papers on a specific task of contextualizing entities of interest from conversation dialogues.
- 2019. NLP for Conversational AI. https://sites.google.com/view/nlp4convai/.Google Scholar
- 2020.RCD-2020 (Retrieval From Conversational Dialogues). https://rcd2020firetask.github.io/RCD2020FIRETASKGoogle Scholar
- 2020. Workshop on Life-long Learning for Spoken Language Systems. https://life-long-nlp.github.io/.Google Scholar
- Eugene Agichtein, Dilek Hakkani-Tür, Surya Kallumadi, and Shervin Malmasi. 2020. ConvERSe'20: The WSDM 2020 Workshop on Conversational Systems for E-Commerce Recommendations and Search (WSDM '20). 897--898.Google Scholar
- Avishek Anand, Lawrence Cavedon, Hideo Joho, Mark Sanderson, and Benno Stein. 2020. Conversational Search (Dagstuhl Seminar 19461). Dagstuhl Reports, Vol. 9, 11 (2020), 34--83.Google Scholar
- Lé a A. Deleris, Debasis Ganguly, Killian Levacher, Martin Stephenson, and Francesca Bonin. 2018. Decision Conversations Decoded. In NAACL-HLT (Demonstrations). Association for Computational Linguistics, 91--95.Google Scholar
- M. Dubiel, Martin Halvey, L. Azzopardi, D. Anderson, and Sylvain Daronnat. 2020. Conversational strategies: impact on search performance in a goal-oriented task.Google Scholar
- Mihail Eric, Rahul Goel, Shachi Paul, Adarsh Kumar, Abhishek Sethi, Peter Ku, Anuj Kumar Goyal, Sanchit Agarwal, Shuyang Gao, and Dilek Hakkani-Tur. 2019. MultiWOZ 2.1: A Consolidated Multi-Domain Dialogue Dataset with State Corrections and State Tracking Baselines. arxiv: 1907.01669 [cs.CL]Google Scholar
- Maria Eskevich, Gareth J. F. Jones, Robin Aly, Roeland Ordelman, Shu Chen, Danish Nadeem, Camille Guinaudeau, Guillaume Gravier, Pascale Sé billot, Tom De Nies, Pedro Debevere, Rik Van de Walle, Petra Galuscá ková, Pavel Pecina, and Martha A. Larson. 2013. Multimedia information seeking through search and hyperlinking. In ICMR. ACM, 287--294.Google Scholar
- Debasis Ganguly, Johannes Leveling, and Gareth J. F. Jones. 2013. An LDA-smoothed relevance model for document expansion: a case study for spoken document retrieval. In SIGIR. ACM, 1057--1060.Google ScholarDigital Library
- Debasis Ganguly, Dipasree Pal, Manisha Verma, and Procheta Sen. 2020. Overview of RCD-2020, the FIRE-2020 Track on Retrieval from Conversational Dialogues. In Proc. of FIRE'20. 33-36.Google ScholarDigital Library
- Ana Valeria Gonzalez, Isabelle Augenstein, and Anders Søgaard. 2019. Retrieval-based Goal-Oriented Dialogue Generation. arxiv: 1909.13717 [cs.CL]Google Scholar
- Alexandru Balan Gustavo Penha and Claudia Hauff. 2019. Introducing MANtIS: a novel Multi-Domain Information Seeking Dialogues Dataset. arxiv: 1912.04639 [cs.CL]Google Scholar
- C. Qu, L. Yang, W. B. Croft, J. Trippas, Y. Zhang, and M. Qiu. 2018. Analyzing and Characterizing User Intent in Information-seeking Conversations. In SIGIR '18.Google Scholar
- David Nicolas Racca and Gareth J. F. Jones. 2016. On the Effectiveness of Contextualisation Techniques in Spoken Query Spoken Content Retrieval. In SIGIR. ACM, 933--936.Google Scholar
- Johanne R. Trippas, Paul Thomas, Damiano Spina, and Hideo Joho. 2020. Third International Workshop on Conversational Approaches to Information Retrieval (CAIR'20): Full-Day Workshop at CHIIR 2020. In Proc. of CHIIR '20. 492--494.Google ScholarDigital Library
- Yongfeng Zhang, Xu Chen, Qingyao Ai, Liu Yang, and W Bruce Croft. 2018. Towards conversational search and recommendation: System ask, user respond. In Proc. of CIKM'18. 177--186.Google ScholarDigital Library
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- Overview of the Supporting and Understanding of Conversational Dialogues (SUD) Workshop
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