A Distributed Approach For Chinese Micro-blog Hot Topic Detection
Xiang Zhang, Ruitao Lin, Lili Dong, Ru Wang
Available Online May 2014.
- https://doi.org/10.2991/lemcs-14.2014.19How to use a DOI?
- Micro-blog; MapReduce; Kmeans clustering; Hidden topic model
- 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.
- 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 -