Automatic Chinese Summarization Method Based on the HowNet and Clustering Algorithm

DOI

10.2991/iske.2007.100How to use a DOI?

Keywords

Automatic Summarization, Clustering,HowNet, Conceptual Vector Space Model, Topic Partition

Abstract

To solve the problems in traditional automatic Chinese summarization, a new method based on the word concept and clustering is presented in this paper. Different from the normal statistical method, concept is used as feature instead of word. Also, instead of word frequency statistics, word concept frequency statistics (WCFS) is used in our approach. For each paragraph, a conceptual vector space model is established, and then the clustering algorithm is used for multiple topic partition. The evaluation results show that the method proposed in this paper is more efficient and robust than the traditional one.

Copyright

© 2007, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Gang Bai
AU  - Dongmei Wang
AU  - Zongyao Ding
AU  - Yi Zhu
PY  - 2007/10
DA  - 2007/10
TI  - Automatic Chinese Summarization Method Based on the HowNet and Clustering Algorithm
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 586
EP  - 590
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.100
DO  - 10.2991/iske.2007.100
ID  - Bai2007/10
ER  -