MURAX: a robust linguistic approach for question answering using an on-line encyclopedia
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Machine Learning
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
The structure and performance of an open-domain question answering system
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
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UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
The lumière project: Bayesian user modeling for inferring the goals and needs of software users
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Actions, answers, and uncertainty: a decision-making perspective on Web-based question answering
Information Processing and Management: an International Journal - Special issue: Bayesian networks and information retrieval
Question answering as question-biased term extraction: a new approach toward multilingual QA
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Semantic chunk annotation for complex questions using conditional random field
KRAQ '08 Coling 2008: Proceedings of the workshop on Knowledge and Reasoning for Answering Questions
A signal-to-noise approach to score normalization
Proceedings of the 18th ACM conference on Information and knowledge management
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SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Web-based question answering: a decision-making perspective
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
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IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
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AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
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We describe a set of supervised machine learning experiments centering on the construction of statistical models of WH-questions. These models, which are built from shallow linguistic features of questions, are employed to predict target variables which represent a user's informational goals. We report on different aspects of the predictive performance of our models, including the influence of various training and testing factors on predictive performance, and examine the relationships among the target variables.