@inproceedings{riedl-biemann-2012-text,
title = "How Text Segmentation Algorithms Gain from Topic Models",
author = "Riedl, Martin and
Biemann, Chris",
editor = "Fosler-Lussier, Eric and
Riloff, Ellen and
Bangalore, Srinivas",
booktitle = "Proceedings of the 2012 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2012",
address = "Montr{\'e}al, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N12-1064",
pages = "553--557",
}
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%0 Conference Proceedings
%T How Text Segmentation Algorithms Gain from Topic Models
%A Riedl, Martin
%A Biemann, Chris
%Y Fosler-Lussier, Eric
%Y Riloff, Ellen
%Y Bangalore, Srinivas
%S Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
%D 2012
%8 June
%I Association for Computational Linguistics
%C Montréal, Canada
%F riedl-biemann-2012-text
%U https://aclanthology.org/N12-1064
%P 553-557
Markdown (Informal)
[How Text Segmentation Algorithms Gain from Topic Models](https://aclanthology.org/N12-1064) (Riedl & Biemann, NAACL 2012)
ACL
- Martin Riedl and Chris Biemann. 2012. How Text Segmentation Algorithms Gain from Topic Models. In Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 553–557, Montréal, Canada. Association for Computational Linguistics.