Satyen Abrol

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According to a recent report by research firm ABI Research, location-based social networks could reach revenues as high as $13.3 billion by 2014 [1]. Social Networks like Foursquare and Gowalla are in a dead heat in the Location War. But, having said that it is important to understand for privacy and security reasons, most of the people on social networking(More)
Geosocial Networking is the new hotness, with social networks providing services and capabilities to the users to associate location to their profiles. But, because of privacy and security reasons, most of the people on social networking sites like Twitter are unwilling to provide locations in their profiles. This creates a need for an algorithm that(More)
Because of privacy and security reasons, most of the people on social networking sites like Twitter are unwilling to specify their locations in the profiles. In this paper, we present a completely novel approach, Tweeque which is a spatio-temporal mining algorithm that predicts the current location of the user purely on the basis of his social network. The(More)
This paper describes a real-time information integration and analytics system called InXite for multi-purpose applications. InXite is designed to detect evolving patterns and trends in streaming data including social media data (e.g., tweets). InXite comprises of multiple modules including InXite Registration and Dashboard, InXite Real-time Data Streamer,(More)
In this talk, we will present how semantics can improve the quality of the data mining process. In particular, first, we will focus on geospatial schema matching with high quality cluster assurance. Next, we will focus on location mining from social network. With regard to the first problem, resolving semantic heterogeneity across distinct data sources(More)
In the present world scenario, everybody is on the lookout for suitable housing options, each having different needs (e.g., the elderly are looking for safe, quiet neighbourhood, while students are looking for affordable apartments close to the university/school). For e.g., Craigslist currently does not have a map version, making the process of apartment(More)
This paper describes a framework, SNODSOC (Stream based novel class detection for social network analysis), that detects evolving patterns and trends in social microblogs. SNODSOC extends our powerful data mining system, SNOD (Stream-based Novel Class Detection) for now detecting novel patterns and trends within microblogs.
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