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conference paper
Diverse Keyword Extraction from Conversations
2013
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics
A new method for keyword extraction from conversations is introduced, which preserves the diversity of topics that are mentioned. Inspired from summarization, the method maximizes the coverage of topics that are recognized automatically in transcripts of conversation fragments. The method is evaluated on excerpts of the Fisher and AMI corpora, using a crowdsourcing platform to elicit comparative relevance judgments. The results demonstrate that the method outperforms two competitive baselines.
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Name
Habibi_ACL_2013.pdf
Type
postprint
Access type
openaccess
License Condition
n/a
Size
335.35 KB
Format
Adobe PDF
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