(Enter summary)
Abstract: The goal of the Web-KB project is to develop automatic methods for constructing and maintaining large knowledge bases whose contents mirror those of the World Wide Web. We argue for the feasibility of a system which, given a manually constructed ontology and a seed knowledge base comprising a set of labeled Web pages, learns to instantiate knowledge-base objects and relations from the Web. Such a system could construct a knowledge base supporting concept-oriented queries to the Web, or serve as ... (Update)
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BibTeX entry: (Update)
Craven, M., DiPasquo, D., Freitag, D., McCallum, A., Mitchell, T., Nigam, K., & Slattery, S. (1998). Learning to extract symbolic knowledge from the World Wide Web. In Proceedings of the Fifteenth National Conference on Artificial Intellligence (AAAI98) , pp. 509--516. http://citeseer.ist.psu.edu/craven98learning.html More
@inproceedings{ craven98learning,
author = "Mark Craven and Dan DiPasquo and Dayne Freitag and Andrew K. McCallum and Tom M. Mitchell and Kamal Nigam and Se{\'{a}}n Slattery",
title = "Learning to extract symbolic knowledge from the {W}orld {W}ide {W}eb",
booktitle = "Proceedings of {AAAI}-98, 15th Conference of the American Association for Artificial Intelligence",
publisher = "AAAI Press, Menlo Park, US",
address = "Madison, US",
pages = "509--516",
year = "1998",
url = "citeseer.ist.psu.edu/craven98learning.html" }
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