Diverse Keyword Extraction from Conversations

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.


Presented at:
Proceedings of the ACL 2013 (51th Annual Meeting of the Association for Computational Linguistics ), Short Papers, Sofia, Bulgaria
Year:
2013
Laboratories:


Note: PRIVATE


 Record created 2013-12-19, last modified 2018-03-17

n/a:
Download fulltext
PDF

Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)