Author(s): R.Gayathri; M.Sobana

The city development is gradually fosters by different functional regions, such as educational areas and business districts. we propose a HPC framework that Finds Regions of different Functions in a city using human mobility , points of interests (POIs) located in a region and check-ins. A city segmented into disjointed regions. The functions of each region are inferred by using a topic-based inference model. By this a region is represented by a distribution of functions, and a function is featured by a distribution of mobility patterns. The intensity of each function is identified for different locations. The results generated by this framework benefits’ a variety of applications. This method is evaluated using large-scale and real-world datasets. The results justify the advantages of our approach over baseline methods solely using POIs or human mobility.