Schedule of Papers and Events

There is growing interest in the automatic extraction of opinions, emotions, and sentiments in text (subjectivity analysis) to support natural language processing applications, ranging from mining product reviews and summarization, to automatic question answering and information extraction. In this talk, I will describe work on two problems in subjectivity analysis at opposite ends of a continuum: subjectivity sense labeling and discourse-level opinion interpretation.

Jan Wiebe is Professor of Computer Science and Director of the Intelligent Systems Program at the University of Pittsburgh. Her research with students and colleagues has been in discourse processing, pragmatics, word-sense disambiguation, and probabilistic classification in NLP. Her most recent work investigates automatically recognizing and interpretating expressions of opinions and sentiments in text, to support NLP applications such as question answering, information extraction, text categorization, and summarization. Her current and past professional roles include ACL Program Co-Chair, NAACL Program Chair, NAACL Executive Board member, Computational Linguistics and Language Resources and Evaluation Editorial Board member, AAAI Workshop Co-Chair, ACM Special Interest Group on Artificial Intelligence (SIGART) Vice-Chair, and ACM-SIGART/AAAI Doctoral Consortium Chair. 

Constraints are everywhere. The popular puzzle Sudoku is an example of a Constraint Satisfaction Problem, where a sample constraint would be "all the numbers in the first row have to be different". Real-world constraint problems can involve reasoning about costs, preferences, uncertainty, and change. Constraints arise in design and configuration, planning and scheduling, diagnosis and testing, and in many other contexts. They define problems in telecommunications, internet commerce, electronics, bioinformatics, transportation, network management, supply chain management, and many other domains. Once problems are modeled as Constraint Satisfaction Problems, constraint satisfaction and optimization methods may help individuals and businesses make satisfactory or even optimal choices when presented with many options and restrictions. The abundance of potential applications multiplies the opportunities to validate and motivate basic research, and to transfer technology for economic and social benefit.

Professor Freuder is the Director of the Cork Constraint Computation Centre in the Department of Computer Science at University College Cork in Ireland. He received his B.A., magna cum laude, in mathematics from Harvard and a Ph.D. in computer science from M.I.T. He has been elected a Fellow of the American Association for the Advancement of Science, the Association for the Advancement of Artificial Intelligence, and the European Coordinating Committee for Artificial Intelligence, and is a Member of the Royal Irish Academy. He received the first Research Excellence Award of the Association for Constraint Programming, and served as Executive Chair of the Organizing Committee of the series of International Conferences on Principles and Practice of Constraint Programming, and as the founding Editor-in-Chief of the Constraints journal. In the Citeseer database of most cited authors in computer science Professor Freuder is ranked in the top one-tenth of one per cent. He has played a key role in obtaining over 60 million dollars in funding from government and industry to support scientific research.