Automatically Determining a Proper Length for Multi-Document Summarization: A Bayesian Nonparametric Approach

Tengfei Ma, Hiroshi Nakagawa


Anthology ID:
D13-1069
Volume:
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing
Month:
October
Year:
2013
Address:
Seattle, Washington, USA
Editors:
David Yarowsky, Timothy Baldwin, Anna Korhonen, Karen Livescu, Steven Bethard
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
736–746
Language:
URL:
https://aclanthology.org/D13-1069
DOI:
Bibkey:
Cite (ACL):
Tengfei Ma and Hiroshi Nakagawa. 2013. Automatically Determining a Proper Length for Multi-Document Summarization: A Bayesian Nonparametric Approach. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pages 736–746, Seattle, Washington, USA. Association for Computational Linguistics.
Cite (Informal):
Automatically Determining a Proper Length for Multi-Document Summarization: A Bayesian Nonparametric Approach (Ma & Nakagawa, EMNLP 2013)
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PDF:
https://aclanthology.org/D13-1069.pdf