SegGen: A Genetic Algorithm for Linear Text Segmentation
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 1647-1651.
Abstract
This paper describes SegGen, a new algorithm for linear text segmentation on general corpuses. It aims to segment texts into thematic homogeneous parts. Several existing methods have been used for this purpose, based on a sequential creation of boundaries. Here, we propose to consider boundaries simultaneously thanks to a genetic algorithm. SegGen uses two criteria: maximization of the internal cohesion of the formed segments and minimization of the similarity of the adjacent segments. First experimental results are promising and SegGen appears to be very competitive compared with existing methods.
@inproceedings{ijcai2007p266,
title = {SegGen: A Genetic Algorithm for Linear Text Segmentation},
author = {Lamprier, Sylvain and Amghar, Tassadit and Levrat, Bernard and Saubion, Frédéric},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {1647--1651},
year = {2007},
url = {https://ijcai.org/proceedings/2007/266},
}
TY - CPAPER TI - SegGen: A Genetic Algorithm for Linear Text Segmentation AU - Lamprier, Sylvain AU - Amghar, Tassadit AU - Levrat, Bernard AU - Saubion, Frédéric T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 1647 EP - 1651 UR - https://ijcai.org/proceedings/2007/266 ER -Copied
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