Electric words: dictionaries, computers, and meanings
Electric words: dictionaries, computers, and meanings
Towards building contextual representations of word senses using statistical models
Corpus processing for lexical acquisition
Machine Learning
Introduction to the special issue on the web as corpus
Computational Linguistics - Special issue on web as corpus
A cascaded finite-state parser for syntactic analysis of Swedish
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Role of word sense disambiguation in lexical acquisition: predicting semantics from syntactic cues
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
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This paper describes the application of a framework for text analysis to the problem of distinguishing unusual or non-standard usage of words in large corpora. The need to identify such novel uses, and augment machine-readable dictionaries is a constant battle for professional lexicographers that need to update their resources in order to keep up with the development of the dynamic and evolving aspects of human language. Of equal importance is the need to devise automatic means upon which we can evaluate to what extent a (defining) dictionary accounts for what we find in corpus data. A combination of both semi-, and automatic means have been explored, and it seems that Machine Learning might be a plausible solution towards the stated goals.