Abstract | ||
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User-centric Internet multimedia scenes challenge us to discover more interesting events and topics based on matching users' needs associated with personal preferences, geographic interests and social norms. Geotagged multimedia contents from online social sites, e.g., Flickr and Twitter, provide large volumes of data about many given locations. Hence, location is one of the most important user-generated contexts and contains rich information about an individual's interests and behavior. Location-based social multimedia streams (e.g., tweets, videos, images) can provide us with socially complementary information to predict users' needs. By making use of geo-tagging, a cohesive set of social multimedia streams can be published to facilitate a more accurate analysis of user-centric big data information and further assess user tastes based on location activities. This tutorial delivers not only a better understanding of the basics of location-aware contextual descriptions and its relations to social multimedia scenes, but may also serve to highlight relationships that can be collaboratively applied to multimodal retrieval and recommendation technology. |
Year | DOI | Venue |
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2013 | 10.1145/2502081.2502236 | ACM Multimedia 2001 |
Keywords | Field | DocType |
social multimedia scene,complementary information,rich information,online social site,geographic-aware multimedia system,geotagged multimedia content,social interaction,user-centric big data information,location-based social multimedia stream,user-centric internet multimedia scene,social norm,social multimedia stream,location based services | World Wide Web,Computer science,Norm (social),Location-based service,Social multimedia,Big data,Multimedia,The Internet | Conference |
Citations | PageRank | References |
5 | 0.68 | 5 |
Authors | ||
2 |
Name | Order | Citations | PageRank |
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Roger Zimmermann | 1 | 14 | 4.18 |
Yi Yu | 2 | 440 | 42.53 |