WordNet: a lexical database for English
Communications of the ACM
Principles of mixed-initiative user interfaces
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Scaling question answering to the Web
Proceedings of the 10th international conference on World Wide Web
Exploiting redundancy in question answering
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic combination of text classifiers using reliability indicators: models and results
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
On the MSE robustness of batching estimators
Proceedings of the 33nd conference on Winter simulation
Using machine learning techniques to interpret WH-questions
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
An analysis of the AskMSR question-answering system
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
From uncertain inference to probability of relevance for advanced IR applications
ECIR'03 Proceedings of the 25th European conference on IR research
A Bayesian approach to learning Bayesian networks with local structure
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Web-based question answering: a decision-making perspective
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
An exploration of the principles underlying redundancy-based factoid question answering
ACM Transactions on Information Systems (TOIS)
A social recommender mechanism for improving knowledge sharing in online forums
Information Processing and Management: an International Journal
Slow Search: Information Retrieval without Time Constraints
Proceedings of the Symposium on Human-Computer Interaction and Information Retrieval
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We present research on methods for generating answers to freely posed questions, based upon information drawn from the Web. The methods exploit the typical redundancy of information on the Web by making multiple queries to search engines and then combining the search results into an answer. We focus on the pursuit of techniques for guiding information gathering in support of answering questions via the learning of probabilistic models that predict the value of information drawn from the Web. We first review research on question-answering systems. Then, we present AskMSR, a prototype Web-based question-answering system. We describe the learning of Bayesian-network models that predict the likelihood that answers are correct, based on multiple observations. We review a two-phased Bayesian analysis and present an expected-utility analysis of information-gathering policies using these inferences. After reviewing the results of a set of experiments, we describe research directions.