SCISOR: extracting information from on-line news
Communications of the ACM
Lexico-semantic pattern matching as a companion to parsing in text understanding
HLT '91 Proceedings of the workshop on Speech and Natural Language
Creating segmented databases from free text for text retrieval
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
An evaluation of phrasal and clustered representations on a text categorization task
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
CONSTRUE/TIS: A System for Content-Based Indexing of a Database of News Stories
IAAI '90 Proceedings of the The Second Conference on Innovative Applications of Artificial Intelligence
Word association norms, mutual information, and lexicography
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
GE: description of the NLTooLSET system as used for MUC-3
MUC3 '91 Proceedings of the 3rd conference on Message understanding
Abstracting of legal cases: the SALOMON experience
Proceedings of the 6th international conference on Artificial intelligence and law
Classification algorithms for NETNEWS articles
Proceedings of the eighth international conference on Information and knowledge management
ACM Transactions on Asian Language Information Processing (TALIP)
Acquisition of Linguistic Patterns for Knowledge-Based Information Extraction
IEEE Transactions on Knowledge and Data Engineering
Feature Reduction and Database Maintenance in NETNEWS Classification
IDEAS '99 Proceedings of the 1999 International Symposium on Database Engineering & Applications
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NLDB, a knowledge-based system that automatically categorizes news stories for dissemination, retrieval, and browsing, is discussed. The major knowledge-based component of NLDB is a lexicosemantic pattern matcher that identifies combinations of words and phrases, as well as more complex patterns. These include word roots, grammatical categories, and semantic structures, such as verbs describing classes of events. It is shown that this linguistic analysis outperforms statistical methods. Because building lexicosemantic patterns can be a laborious process, a set of statistical methods that automate pattern acquisition while preserving the benefits of a knowledge-based approach are developed.