A Distributed Approach For Chinese Micro-blog Hot Topic Detection

DOI

10.2991/lemcs-14.2014.19How to use a DOI?

Keywords

Micro-blog; MapReduce; Kmeans clustering; Hidden topic model

Abstract

In consideration of the features of micro-blogging content such as short text, sparse feature words and the huge scale, a method to detect micro-blogging hot topic was proposed in this paper based on MapReduce programming model. This method first employs the hidden topic analysis to solve the problem of short micro-blogging content and sparse feature words. Then the CURE algorithm is used to alleviate the problem that the Kmeans algorithm is sensitive to the initial points. Finally, the hot topic clustering results are obtained through the parallel Kmeans clustering algorithm based on the MapReduce programming model. The experimental results show that proposed method can effectively improve the micro-blogging hot topic detection efficiency.

Copyright

© 2014, 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  - Xiang Zhang
AU  - Ruitao Lin
AU  - Lili Dong
AU  - Ru Wang
PY  - 2014/05
DA  - 2014/05
TI  - A Distributed Approach For Chinese Micro-blog Hot Topic Detection
BT  - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science
PB  - Atlantis Press
SP  - 81
EP  - 85
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-14.2014.19
DO  - 10.2991/lemcs-14.2014.19
ID  - Zhang2014/05
ER  -