Publication | Open Access
Identifying topics by position
269
Citations
7
References
1997
Year
Unknown Venue
EngineeringIntelligent Information RetrievalCorpus LinguisticsText MiningAutomatic SummarizationNatural Language ProcessingInformation RetrievalText SummarizationComputational LinguisticsDocument ClassificationLanguage StudiesContent AnalysisLikely TopicsKnowledge DiscoveryInformation ExtractionAutomated TrainingTopic ModelOptimal Position PolicyKeyword ExtractionText ProcessingLinguistics
This paper addresses the problem of identifying likely topics of texts by their position in the text. It describes the automated training and evaluation of an Optimal Position Policy, a method of locating the likely positions of topic-bearing sentences based on genre-specific regularities of discourse structure. This method can be used in applications such as information retrieval, routing, and text summarization.
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