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Capturing Cross-Domain Ripples

  • Suman Deb RoyEmail author
  • Wenjun Zeng
Chapter
  • 661 Downloads

Abstract

Various web domains present original, updated or aggregated multimedia content for users. Media on the Internet is unevenly distributed into domains depending on platforms, popularity and bias. The domain where it originates limits its power. For example, video popularity is usually judged by view count but not by how trending the video topic is on another domain. Similarly, Twitter users can only see related media shared in Twitter, but not from external sources. This compels users to perform unguided search in external resources manually. Such video sites are more often than not filled with an explosion of video/image information. Thus the need for better cross-domain media recommendation systems is considered to be a key constituent to social search and empowering online media.

Keywords

Topic Modeling Latent Dirichlet Allocation Auxiliary Data Feature Word Social Topic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.BetaworksNew YorkUSA
  2. 2.Department of Computer ScienceUniversity of MissouriColumbiaUSA

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