Learning to Extract Symbolic Knowledge from the World Wide Web

Learning to Extract Symbolic Knowledge from the World Wide Web (1998)

Cached

Download Links

Other Repositories/Bibliography

DBLP

by Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew McCallum, Tom Mitchell, Kamal Nigam, Sean Slattery

Citations:

290 - 24 self

BibTeX

@MISC{Craven98learningto,
    author = {Mark Craven and Dan DiPasquo and Dayne Freitag and Andrew McCallum and Tom Mitchell and Kamal Nigam and Sean Slattery},
    title = {Learning to Extract Symbolic Knowledge from the World Wide Web},
    year = {1998}
}

Bookmark

OpenURL

Abstract

The World Wide Web is a vast source of information accessible to computers, but understandable only to humans. The goal of the research described here is to automatically create a computer understandable world wide knowledge base whose content mirrors that of the World Wide Web. Such a

Citations

6514	Elements of Information Theory - Cover, Thomas - 1991
1180	and Biing-Hwang Juang. Fundamentals of speech recognition - Rabiner - 1993
946	Combining labeled and unlabeled data with co-training - Blum, Mitchell - 1998
800	Fast effective rule induction - Cohen - 1995
784	Learning logical definitions from relations - Quinlan - 1989
619	Nigam K: A comparison of event models for naïve Bayes text classification - McCallum - 1998
516	Letizia: An Agent that Assists Web Browsing - Lieberman - 1995
486	Pazzani M: On the optimality of the simple Bayesian classifier under zero-one loss - Domingos - 1997
460	Wrapper induction for information extraction - Kushmerick, Weld, et al. - 1997
365	A sequential algorithm for training text classifiers - Lewis, Gale - 1994
363	Sahami M: Hierarchically classifying documents using very few words - Koller - 1997
353	Newsweeder: Learning to filter netnews - Lang - 1995
301	Toward optimal feature selection - Koller, Sahami - 1996
290	Webwatcher: A tour guide for the world wide web - Joachims, Freitag, et al. - 1997
285	A probabilistic analysis of the rocchio algorithm with tfidf for text categorization - Joachims - 1997
279	Doorenbos, “A Scalable Comparison Shopping Agent for The World Wide Web - Etzioni, Weld, et al. - 1996
277	Bottom-up relational learning of pattern matching rules for information extraction - Califf, Mooney - 2003
271	Syskill and Webert: Identifying Interesting Web Sites - Pazzani, Muramatsu, et al. - 1996
244	Automatically generating extraction patterns from untagged text - Riloff - 1996
239	Comparison of Two Learning Algorithms for Text Categorization - Lewis, Ringuette - 1994
225	Silk from a sow’s ear: Extracting usable structures from the Web - Pirolli, Pitkow, et al. - 1996
216	Training algorithms for linear text classi ers - Lewis, Shapire, et al. - 1996
207	Automated learning of decision rules for text categorization - Apte, Damerau, et al. - 1994
198	Employing EM and pool-based active learning for text classification - McCallum, Nigam - 1998
195	The zero-frequency problem: estimating the probabilities of novel events in adaptive text compression - Witten, Bell - 1991
186	Cameron-Jones. FOIL: A midterm report - Quinlan, M - 1993
147	Estimating Probabilities: A Crucial Task in Machine Learning - Cestnik - 1990
147	A Comparison of Classifiers and Document Representations for the Routing Problem - Schutze, Hull, et al. - 1995
140	Learning to classify text from labeled and unlabeled documents - Nigam, McCallum, et al. - 1998
134	Information Extraction from HTML: Application of a General MachineLearning Approach - Freitag - 1998
119	EXtensible Markup Language (XML) 1.0 - Bray, Paoli, et al. - 2000
116	Learning information retrieval agents: Experiments with automated web browsing. On-line Working - Balabonovic, Shoham
109	Ontology-based Web Agents - Luke, Spector, et al. - 1997
106	Learning to extract text-based information from the World Wide Web - Soderland - 1997
91	ParaSite: mining structural information on the web - Spertus - 1997
79	Towards Language Independent Automated Learning of Text Categorization Models - Apté, Damerau, et al. - 1994
79	Learning logical de nitions from relations - Quinlan - 1990
78	Classifying news stories using memory based reasoning - Masand, Linoff, et al. - 1992
78	Models for retrieval with probabilistic indexing - Fuhr - 1989
76	Multi-strategy learning for information extraction - Freitag - 1998
75	Category translation: Learning to Understand Information on the internet - Etzioni, Perkowitz - 1995
73	An empirical study of automated dictionary construction for information extraction in three domains - Riloff - 1996
58	Handling noise in inductive logic programming - Dzeroski - 1991
58	From sentence processing to information access on the world wide web - Katz - 1997
56	Learning relations by pathfinding - Richards, Mooney - 1992
55	Dynamic reference sifting: A case study in the homepage domain - Shakes, Langheinrich, et al. - 1997
55	Feature selection in statistical learning of text categorization - Yang, Pederson - 1997
44	Combining statistical and relation methods for learning in hypertext domains - Slattery, Craven - 1998
42	Toward General-Purpose Learning for Information Extraction - Freitag - 1998
41	A case study in using linguistic phrases for text categorization on the WWW - Furnkranz, Mitchell, et al. - 1998