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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...
In multi-media and social media communities, web topic detection poses two main difficulties that conventional approaches can barely handle: 1) there are large inter-topic variations among web topics; 2) supervised information is rare to identify the real topics. In this paper, we address these problems from the similarity diffusion perspective among objects on web, and present a clustering-like pattern...
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