A Topic Detection Method Based on KeyGraph and Community Partition-Reference-Cited by-同舟云学术

A Topic Detection Method Based on KeyGraph and Community Partition

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2018 International Conference on Computing and Artificial Intelligence - ICCAI 2018
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Author:

Yang Shanliang¹,Sun Qi¹,Zhou Huyong¹,Gong Zhengjie¹,Zhou Yangzhi¹,Huang Junhong¹

Affiliation:

1. Institute of Media Science, Communication University of China, Beijing, P.R. China

Publisher

ACM Press

Reference16 articles.

1. Siti Rofiqoh Fitriyani, Hendri Murfi. 2016. The K-Means with Mini Batch Algorithm for Topics Detection on Online News. 2016 Fourth International Conference on Information and Communication Technologies.

2. Danfeng Yan, Enzheng Hua, Bo Hu. 2016. An Improved Single-Pass Algorithm for Chinese Microblog Topic Detection and Tracking. 2016 IEEE International Congress on Big Data, 251--258.

3. Xiao Hu. 2016. News Hotspots Detection and Tracking Based on LDA Topic Model. 2016 International Conference on Progress in Informatics and Computing, 248--252.

4. Yukio Ohsawa, Nels E. Benson, Masahiko Yachida. 1998. KeyGraph: Automatic Indexing by Co-occurrence Graph based on Building Construction Metaphor. IEEE International forum on Research and technology advances in digital libraries, 1998. ADL98. Poceedings, 12--18.

5. Kasun Perera, Damitha Karunarathne. 2015. KeyGraph and WordNet Hypernyms for Topic Detection. 2015 12th International Joint Conference on Computer Science and Software Engineering (JCSSE), 22--24.

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