The 4th International Workshop on Search-Oriented Conversational AI (SCAI)
at IJCAI-19, Macao 🇲🇴, China, August 12
IJCAI early registration is June 20, 2019 (UTC-12)
Click here to go to the SCAI main page.
More and more information is found and consumed in a conversational form rather than using traditional search engines. Chatbots, personal assistants in our phones and eyes-free devices are being used increasingly more for different purposes, including information retrieval and exploration. On the other side, information retrieval empowers dialogue systems to answer questions and to get context for assisting the user in her tasks. With the recent success of deep learning in different areas of natural language processing, this appears to be the right foundation to power search conversationalization. Yet, we believe more can be done for theory and practice of conversation-based search and search-based dialogues.
The aim of this edition of the SCAI workshop is to bring together researchers from the Natural Language Processing (NLP), Artificial Intelligence (AI), and Information Retrieval (IR) communities to investigate future directions of research in the area of search-oriented conversational systems. The focus of this installment seeks to broaden participation between research and industry. The previous instances identified a number of research areas related which warrant additional deeper exploration. To provide a broad forum we solicit a variety of research and position paper submissions.
The 1st edition of the workshop was co-located with International Conference on the Theory of Information Retrieval (ICTIR 2017).
The 2nd edition of the workshop was co-located with the Conference on Emperical Methods in Natural Language Processing (EMNLP 2018).
The 3rd edition (special half-day edition) of the workshop was co-located with The Web Conference 2019 (TheWebConf 2019).
Surfacing search results or other information in form of a dialogue how to present information coming from search in a form of a dialogue how ensure smooth transition between dialog turns which model to use for dialog-state tracking
Evaluation of Search-Oriented Conversational AI — From Conversational AI to Personal Assistants
Personalization for conversational AI and for its evaluation
Deep Learning for Conversational AI
(Deep) Reinforcement Learning for Conversational AI
Voice as Input (when we consider not only text input, but also voice interactions with the agent — how will it affect existing models?)
Specialized applications and uses cases for conversational search (specialized domains in health, finance, travel, etc.)