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Learning to Extract Symbolic Knowledge from the World Wide Web (1998)  (Make Corrections)  (149 citations)
Mark Craven, Dayne Freitag, Andrew McCallum Tom Mitchell, Kamal Nigam, Choon Yang Quek
Proceedings of AAAI-98, 15th Conference of the American Association for Artificial Intelligence



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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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