Information extraction and text summarization using linguistic knowledge acquisition
Information Processing and Management: an International Journal
Selection and information: a class-based approach to lexical relationships
Selection and information: a class-based approach to lexical relationships
Semantic feature extraction from technical texts with limited human intervention
Semantic feature extraction from technical texts with limited human intervention
Improved portability and parsing through interactive acquisition of semantic information
ANLC '88 Proceedings of the second conference on Applied natural language processing
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
MUC4 '92 Proceedings of the 4th conference on Message understanding
The acquisition of lexical semantic knowledge from large corpora
HLT '91 Proceedings of the workshop on Speech and Natural Language
Smoothing of automatically generated selectional constraints
HLT '93 Proceedings of the workshop on Human Language Technology
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Semantic clusters of a domain form an important feature that can be useful for performing syntactic and semantic disambiguation. Several attempts have been made to extract the semantic clusters of a domain by probabilistic or taxonomic techniques. However, not much progress has been made in evaluating the obtained semantic clusters. This paper focuses on an evaluation mechanism that can be used to evaluate semantic clusters produced by a system against those provided by human experts.