Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science

A Distributed Approach For Chinese Micro-blog Hot Topic Detection

Authors
Xiang Zhang, Ruitao Lin, Lili Dong, Ru Wang
Corresponding Author
Xiang Zhang
Available Online May 2014.
DOI
https://doi.org/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.
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Proceedings
International Conference on Logistics Engineering, Management and Computer Science (LEMCS 2014)
Part of series
Advances in Intelligent Systems Research
Publication Date
May 2014
ISBN
978-94-6252-010-3
ISSN
1951-6851
DOI
https://doi.org/10.2991/lemcs-14.2014.19How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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  - International Conference on Logistics Engineering, Management and Computer Science (LEMCS 2014)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-14.2014.19
DO  - https://doi.org/10.2991/lemcs-14.2014.19
ID  - Zhang2014/05
ER  -