Class-based n-gram models of natural language
Computational Linguistics
The Cluster Dissection and Analysis Theory FORTRAN Programs Examples
The Cluster Dissection and Analysis Theory FORTRAN Programs Examples
Simulation and the Monte Carlo Method
Simulation and the Monte Carlo Method
Information Retrieval
Co-occurrences of antonymous adjectives and their contexts
Computational Linguistics
Acquiring disambiguation rules from text
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
Text filtering in MUC-3 and MUC-4
MUC4 '92 Proceedings of the 4th conference on Message understanding
Unsupervised data processing for classifier-based speech translator
Computer Speech and Language
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Our work focuses on identifying various types of lexical data in large corpora through statistical analysis. In this paper, we present a method for grouping adjectives according to their meaning, as a step towards the automatic identification of adjectival scales. We describe how our system exploits two sources of linguistic knowledge in a corpus to compute a measure of similarity between two adjectives, using statistical techniques and a clustering algorithm for grouping. We evaluate the significance of the results produced by our system for a sample set of adjectives.