Speech Communication - Special issue on interactive voice technology for telecommunication applications (IVITA '96)
A vector space model for automatic indexing
Communications of the ACM
Implementation of the SMART Information Retrieval System
Implementation of the SMART Information Retrieval System
Applied morphological processing of English
Natural Language Engineering
Finding content-bearing terms using term similarities
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Enriching the knowledge sources used in a maximum entropy part-of-speech tagger
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
Technical support dialog systems: issues, problems, and solutions
NAACL-HLT-Dialog '07 Proceedings of the Workshop on Bridging the Gap: Academic and Industrial Research in Dialog Technologies
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To detect and describe categories in a given set of utterances without supervision, one may apply clustering to a space therein representing the utterances as vectors. This paper compares hard and fuzzy word clustering approaches applied to `almost' unsupervised utterance categorization for a technical support dialog system. Here, `almost' means that only one sample utterance is given per category to allow for objectively evaluating the performance of the clustering techniques. For this purpose, categorization accuracy of the respective techniques are measured against a manually annotated test corpus of more than 3000 utterances.