Uncertainty in Artificial Intelligence
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Web-Based Question Answering: A Decision-Making Perspective
David Azari, Eric Horvitz, Susan Dumais, Eric Brill
Abstract:
We describe an investigation of the use of probabilistic models and cost-benefit analyses to guide resource-intensive procedures used by a Web-based question answering system. We first provide an overview of research on question-answering systems. Then, we present details on AskMSR, a prototype web-based question answering system. We discuss Bayesian analyses of the quality of answers generated by the system and show how we can endow the system with the ability to make decisions about the number of queries issued to a search engine, given the cost of queries and the expected value of query results in refining an ultimate answer. Finally, we review the results of a set of experiments.
Keywords:
Pages: 11-19
PS Link:
PDF Link: /papers/03/p11-azari.pdf
BibTex:
@INPROCEEDINGS{Azari03,
AUTHOR = "David Azari and Eric Horvitz and Susan Dumais and Eric Brill",
TITLE = "Web-Based Question Answering: A Decision-Making Perspective",
BOOKTITLE = "Proceedings of the Nineteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-03)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2003",
PAGES = "11--19"
}


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