Unsupervised Web Topic Detection Using A Ranked Clustering-Like Pattern Across Similarity Cascades
文献类型:期刊论文
作者 | junbiao pang![]() ![]() |
刊名 | IEEE Transactions on Multimedia
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出版日期 | 2015 |
卷号 | 17期号:6页码:843-853 |
关键词 | Maximal Clique Poisson Deconvolution Similarity Cascade Unsupervised Ranking Web Topic Detection |
英文摘要 | Despite 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. |
源URL | [http://ir.ia.ac.cn/handle/173211/15388] ![]() |
专题 | 自动化研究所_类脑智能研究中心 |
推荐引用方式 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. |
入库方式: OAI收割
来源:自动化研究所
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