Automatically Selecting Useful Phrases for Dialogue Act Tagging

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dc.creatorSamuel, Ken
dc.creatorCarberry, Sandra
dc.creatorVijay-Shanker, K.
dc.date1999-06-18
dc.date.accessioned2026-07-07T03:24:09Z
dc.date.available2026-07-07T03:24:09Z
dc.descriptionWe present an empirical investigation of various ways to automatically identify phrases in a tagged corpus that are useful for dialogue act tagging. We found that a new method (which measures a phrase's deviation from an optimally-predictive phrase), enhanced with a lexical filtering mechanism, produces significantly better cues than manually-selected cue phrases, the exhaustive set of phrases in a training corpus, and phrases chosen by traditional metrics, like mutual information and information gain.
dc.description14 pages, published in PACLING'99
dc.identifierhttps://arxiv.org/abs/cs/9906016
dc.identifierhttp://arxiv.org/abs/cs/9906016
dc.identifierSamuel, Ken and Carberry, Sandra and Vijay-Shanker, K. 1999. Automatically Selecting Useful Phrases for Dialogue Act Tagging. In Proceedings of the Fourth Conference of the Pacific Association for Computational Linguistics. Waterloo, Ontario, Canada
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/33216
dc.subjectArtificial Intelligence
dc.subjectMachine Learning
dc.subjectI.2.7; I.2.6
dc.titleAutomatically Selecting Useful Phrases for Dialogue Act Tagging
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