Tree Model Optimized for Precisely Predicting Location-Based Services from User Behavior Data
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A social network is a collection of individuals connected by one or more types of relationships, such as friendship, shared knowledge, and common interest. Location data adds strength to social networks. A space can be specified as relative, absolute, and symbolic. Location is commonly referred to as three types of geographical representations a point, a region, and a trend. In recent times, localization strategies enhance social networking services and allow users to share their location-related content, geo-tagged photos and notes. This is known as location-based social networks (LBSNs). Thi...
A social network is a collection of individuals connected by one or more types of relationships, such as friendship, shared knowledge, and common interest. Location data adds strength to social networks. A space can be specified as relative, absolute, and symbolic. Location is commonly referred to as three types of geographical representations a point, a region, and a trend. In recent times, localization strategies enhance social networking services and allow users to share their location-related content, geo-tagged photos and notes. This is known as location-based social networks (LBSNs). This chapter also includes a brief review on the available techniques. Further, the discussion on various methodologies to be applied on different datasets with related existing requirements.
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