Automatic Chinese Summarization Method Based on the HowNet and Clustering Algorithm
Gang Bai1, Dongmei Wang, Zongyao Ding, Yi Zhu
1College of Information Technical Science, Nankai University
Available Online October 2007.
- 10.2991/iske.2007.100How to use a DOI?
- Automatic Summarization, Clustering,HowNet, Conceptual Vector Space Model, Topic Partition
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.
- © 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/).
Cite this article
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 -