A Clustering Algorithm towards Microblogs based on Vector Space Model

DOI

10.2991/citcs.2012.243How to use a DOI?

Keywords

microblogs clustering, k-means, vector space model

Abstract

Weibos have become wildly popular in China in recent years, and state media reports that there are more than 300 million registered users. The Real Name Policy[1] requires all users on Chinese weibo websites to register with the name that corresponds with their government issued ID card. With the rapid development of the web, the research of consensus encounters new problems and challenges. Is a practical method for large-scale text clustering, instant messaging, text content analysis features, and find or track the social hot topics. Unlike the file, which is not suitable for very common clustering algorithm' A new method is proposed of the named MVSM synthesis microblogging dialogue, but also enriched the words of the vector is not included in the text of the blog, but existing content is closely related. Extended vector space this MVSM perform the dialogue, k-means clustering. Experiments on public datasets show better, MVSM than traditional k-means and kmeans algorithm into two

Copyright

© 2012, 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  - Guoyou Chen
AU  - Jiajia Miao
AU  - Handong Mao
AU  - Le Wang
AU  - Siyu Jiang
PY  - 2012/11
DA  - 2012/11
TI  - A Clustering Algorithm towards Microblogs based on Vector Space Model
BT  - Proceedings of the 2012 National Conference on Information Technology and Computer Science
PB  - Atlantis Press
SP  - 955
EP  - 958
SN  - 1951-6851
UR  - https://doi.org/10.2991/citcs.2012.243
DO  - 10.2991/citcs.2012.243
ID  - Chen2012/11
ER  -