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Unsupervised Web Topic Detection Using A Ranked Clustering-Like Pattern Across Similarity Cascades
junbiao pang; Fei Jia; Chunjie Zhang; Weigang Zhang; Qingming Huang; Baocai Yin
Source PublicationIEEE Transactions on Multimedia
2015
Volume17Issue:6Pages:843-853
AbstractDespite the massive growth of social media on
the Internet, the process of organizing, understanding, and
monitoring user generated content (UGC) has become one
of the most pressing problems in today’s society. Discovering
topics on the web from a huge volume of UGC is one of the
promising approaches to achieve this goal. Compared with
classical topic detection and tracking in news articles, identifying
topics on the web is by no means easy due to the noisy, sparse,
and less-constrained data on the Internet. In this paper, we
investigate methods from the perspective of similarity diffusion,
and propose a clustering-like pattern across similarity cascades
(SCs). SCs are a series of subgraphs generated by truncating a
similarity graph with a set of thresholds, and then maximal cliques
are used to capture topics. Finally, a topic-restricted similarity
diffusion process is proposed to efficiently identify real topics from
a large number of candidates. Experiments demonstrate that
our approach outperforms the state-of-the-art methods on three
public data sets.
KeywordMaximal Clique Poisson Deconvolution Similarity Cascade Unsupervised Ranking Web Topic Detection
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/15388
Collection类脑智能研究中心
Recommended Citation
GB/T 7714
junbiao pang,Fei Jia,Chunjie Zhang,et al. Unsupervised Web Topic Detection Using A Ranked Clustering-Like Pattern Across Similarity Cascades[J]. IEEE Transactions on Multimedia,2015,17(6):843-853.
APA junbiao pang,Fei Jia,Chunjie Zhang,Weigang Zhang,Qingming Huang,&Baocai Yin.(2015).Unsupervised Web Topic Detection Using A Ranked Clustering-Like Pattern Across Similarity Cascades.IEEE Transactions on Multimedia,17(6),843-853.
MLA junbiao pang,et al."Unsupervised Web Topic Detection Using A Ranked Clustering-Like Pattern Across Similarity Cascades".IEEE Transactions on Multimedia 17.6(2015):843-853.
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