Exploiting temporal topic models in social media retrieval
Tuan Tran · 2012
Many of user generated contents in the Web 2.0 center around real-world incidents such as Japanese tsunami, or general concerns such as recent economic downturn. Such type of information is always of interest to users. For instance, when a user reads a news article about a tsunami in Japan, she wants to see related Flickr photos or more tweets about it. Conventional keyword-based search is inappropriate, since it is not always trivial to formulate ad-hoc interests about the event and material. In some cases, the user might want to explore emerging topics that dominate different sources. Present systems fail to connect topically documents across media, and the user has to examine individual sources to infer the topics herself.