Nowadays, intelligent information systems, especially the interactive information systems (conversational interaction systems; news feed recommender systems, and interactive search engines, etc.), are ubiquitous in real-world applications. These systems either converse with users explicitly through natural languages, or mine users interests and respond to users requests implicitly. Interactivity has become a crucial element towards intelligent information systems. Despite the fact that interactive information systems have gained significant progress, there are still many challenges to be addressed when applying these models to real-world scenarios. This half day workshop explores challenges and potential research, development, and application directions in applied interactive information systems. We aim to discuss the issues of applying interactive information models to production systems, as well as to shed some light on the fundamental characteristics, i.e., interactivity and applicability, of different interactive tasks. We welcome practical, theoretical, experimental, and methodological studies that advances the interactivity towards intelligent information systems. The workshop aims to bring together a diverse set of practitioners and researchers interested in investigating the interaction between human and information systems to develop more intelligent information systems.
|Jul 30 08:30-08:35||Opening|
|Jul 30 08:35-09:35||Keynote (Grounded Text Generation for Robust Conversational AI)|
|Jul 30 09:35-10:35||Keynote (Recent Research on Conversational Recommender System)|
|Jul 30 10:35-12:00||Paper presentations|
Attribute-aware Diversification for Sequential Recommendations
Anton Steenvoorden, Emanuele Di Gloria, Wanyu Chen, Pengjie Ren and Maarten de Rijke
From A Glance to “Gotcha”: Interactive Facial Image Retrieval with Progressive Relevance Feedback
Xinru Yang, Haozhi Qi, Mingyang Li and Alexandar Hauptmann
Continuous click behavior in academic search environment
Zhu Liang, Chuan Jiang, Dongbo Wang and Si Shen
Topic-diversified Neural Dialogue Generation
Hengyi Cai, Hongshen Chen, Xiaofang Zhao, Dawei Yin, Zhuoye Ding, Yongjun Bao and Weipeng Yan
Continue or SHIFT: Learning Conversational Patterns for Dialogue Generation
Shaoxiong Feng, Xuancheng Ren, Kan Li and Xu Sun
Constructing Transparent QA Chatbot based on the Official Website Documents
Wataru Sakata, Ribeka Tanaka and Sadao Kurohashi
Research Scientist at Data Science Lab, JD.com
Professor at Shandong University.
Postdoctoral researcher at the Information and Language Processing Systems (ILPS) group, University of Amsterdam.
Director of Search Science at Baidu.
Vice President of Technology of JD.COM Inc., Deputy Managing Director of JD AI Research, and Head of the Deep learning, NLP and Speech Lab