We are pleased to announce that Professor Bing Liu of University of Illinois, Chicago will give a keynote speech at the workshop.
Bio: Bing Liu is a Professor of Computer Science at the University of Illinois at Chicago (UIC). He obtained his PhD in Artificial Intelligence from the University of Edinburgh. Before joining UIC in 2002, he was with the National University of Singapore. He has published extensively in the fields of data mining, Web mining and opinion mining in leading conferences and journals. His research has been focused on classification based on associations, interestingness in data mining, learning from positive and unlabeled examples, Web data/information extraction, and opinion mining and sentiment analysis. He has also written a textbook titled "Web Data Mining: Exploring Hyperlinks, Contents and Usage Data". On professional services, Liu has served as associate editors of IEEE Transactions on Knowledge and Data Engineering, and SIGKDD Explorations, and is in the editorial boards of several other journals. He also served or serves as program chairs of IEEE International Conference on Data Mining (ICDM-2010), ACM Conference on Web Search and Data Mining (WSDM-2010), ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2008), SIAM Conference on Data Mining (SDM-2007), ACM Conference on Information and Knowledge Management (CIKM-2006), and Pacific Asia Conference on Data Mining (PAKDD-2002), and as area chairs of International World Wide Web Conference (WWW-2005, WWW-2010) in charge of the data mining track. In addition, he has served extensively as program committee members, and senior program committee members of leading conferences in data mining, Web technologies and natural language progressing.
With the rapid growth of Web 2.0, the Internet has become an excellent source for gathering the voice of the public. People are now encouraged to post reviews of products or express their views on almost everything on bulletin boards, Internet forums, news groups, etc. These word-of-mouth discussions provide valuable source of knowledge for both information promulgators and readers. However, it is an extremely daunting and time-consuming task for the users to sift through the sheer volume of user-generated content in order to distill useful knowledge and then act accordingly.
The academic community as well as practitioners have recognized the importance of opinion mining, and are working on various approaches to facilitate automated opinion analysis and knowledge discovery from user-generated contents. The research on opinion mining is highly inter-disciplinary and its success depends on advances in all related fields. As such, this workshop aims to provide a forum to foster the communication and interaction between researchers and practitioners from all related computer science, business, and social science disciplines, including but not limited to, data mining, information retrieval, Web, natural language processing, marketing, an linguistics.
Suggested topics of this workshop include, but are not limited to:
- Opinion retrieval, extraction, categorization, and summarization
- Topic-sentiment analysis
- Sentiment identification and filtering
- Domain-driven opinion mining and sentiment analysis
- Economic value of user-generated contents
- Recommender systems
- Evaluation methodologies
- Performance issues, scalability and efficiency
- Applications in different contexts (e.g., politics, business intelligence, sociology, and marketing research)
The Workshop proceedings volume will be published by IEEE Computer Society Press, to be indexed by EI. All accepted contributions will be included in the volume. The best papers from the workshop may get the recommendation and support from members of the Program Committee to submit extended versions of their work to leading journals in the field.
Regular research papers reporting original scientific results, as well as vision and work-in-progress papers that have the potential to stimulate debate on existing solutions or identify emerging challenges are encouraged. All submitted papers will be reviewed by program committee members on the basis of technical quality, relevance, significance, and clarity. Paper submissions should be limited to a maximum of 4 pages (only one additional page is allowed and extra payment is required for the additional page). The papers must be in English and should be formatted according to the IEEE 2-column format (see the Author Guidelines at http://www.yorku.ca/wiiat10/submissions.php). The workshop only accepts on-line submissions. Please use the Workshop Submission Page on the WI-IAT'2010 website to submit your paper. The authors of accepted contributions will be asked to submit final version and register for the conference.
|Due date for full workshop papers submission:|
|Notification of paper acceptance to authors:||June 7, 2010|
|Camera-ready deadline for accepted papers:||June 21, 2010|
|Workshop day:||August 31, 2010|
Workshop General Chair
Nick Koudas, University of Toronto & Sysomos Inc.
Shlomo Argamon, Illinois Institute of Technology
Lee Hyun Chul, University of Toronto and Thoora Inc.
Anindya Ghose, New York University
Yue Lu, UIUC
Bo Pang, Yahoo
Ken Pu, University of Ontario Institute of Technology
Stuart W. Shulman, University of Massachusetts Amherst
Yabo Xu, Sun Yat-sen University
Bei Yu, Syracuse University
Daniel Dajun Zeng, Chinese Academy of Sciences and University of Arizona
Location: TEL 0009, York University
Session A (8:35-10:00)
- Workshop Opening
- Keynote: Opinion Mining: Structure the Unstructured, Bing Liu
- Invited Talk: Measuring Validity in Human and Machine Annotation, Stuart W. Shulman
- Tutorial: An Introduction to the Public Comment Analysis Toolkit (PCAT), Stuart W. Shulman
Session B (10:20-12:00)
- Assessing the Quality of Opinion Retrieval Systems, Giambattista Amati, Giuseppe Amodeo, Valerio Capozio, Giorgio Gambosi, and Carlo Gaibisso
- Mining Customer Feedbacks for Actionable Intelligence, Lipika Dey, Sk Mirajul Haque, and Nidhi Raj
- An Unsupervised Snippet-Based Sentiment Classification Method for Chinese Unknown Phrases Without Using Reference Word Pairs, Ting-Chun Peng and Chia-Chun Shih
- Semi-Supervised Learning for Opinion Detection, Ning Yu and Sandra Kubler
- Workshop Closing Remarks
For all questions regarding local organization, registration and the main WI-IAT'2010 conference please refer to contacts at main WI-IAT 2010 Website(s).
For questions specific to the OMBI
Workshop please contact:
Dr Xiaohui Yu
School of Information Technology, York University
4700 Keele Street
Toronto, ON, Canada, M3J 1P3
Fax: (+1) 416-736-5287
Tel: (+1) 416-736-2100 ext 33887