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Previous research on online media popularity prediction concluded that the rise in popularity of online videos maintains a conventional logarithmic distribution. However, recent studies have shown that a significant portion of online videos exhibit bursty/sudden rise in popularity, which cannot be accounted for by video domain features alone. In this paper, we propose a novel transfer learning framework...
This paper aims to connect social media from disparate sources on the Internet by building a common topic space in-between, using which cross domain media recommendations can be realized on the web. The topic space is built and updated in real time by extending the Latent Dirichlet Allocation (LDA) model to cater to streaming online data. Our topical model, named Online Streaming LDA (OSLDA), is able...
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