A scalable comparison-shopping agent for the World-Wide Web
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Relational learning of pattern-match rules for information extraction
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Learning Logical Definitions from Relations
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Wrapper induction for information extraction
Wrapper induction for information extraction
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COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Learning to remove Internet advertisements
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SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Hierarchical Wrapper Induction for Semistructured Information Sources
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EMCL '01 Proceedings of the 12th European Conference on Machine Learning
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OOIS '02 Proceedings of the Workshops on Advances in Object-Oriented Information Systems
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PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
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Information Extraction from HTML: Combining XML and Standard Techniques for IE from the Web
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Adaptive information extraction from text by rule induction and generalisation
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Because the World Wide Web consists primarily of text, information extraction is central to any effort that would use the Web as a resource for knowledge discovery. We show how information extraction can be cast as a standard machine learning problem, and argue for the suitability of relational learning in solving it. The implementation of a general-purpose relational learner for information extraction, SRV, is described. In contrast with earlier learning systems for information extraction, SRV makes no assumptions about document structure and the kinds of information available for use in learning extraction patterns. Instead, structural and other information is supplied as input in the form of an extensible token-oriented feature set. We demonstrate the effectiveness of this approach by adapting SRV for use in learning extraction rules for a domain consisting of university course and research project pages sampled from the Web. Making SRV Web-ready only involves adding several simple HTML-specific features to its basic feature set.