EAGER: Data Analytics over Location Based Services

University Of Texas At Arlington, Arlington TX

Investigators

Abstract

Location Based Services are extremely popular, with millions of users making daily use of mapping services such as Google and Bing maps, as well as location based features integrated into numerous other systems such as Twitter and Yelp. Data analytics over the backend databases of these services can reveal interesting "big picture" information, such as geographic distribution of points of interest and regional variation in user behavior. In this project we show that such interesting data analytics can be performed by users whose access to the databases is limited via the available programming and query interfaces. The research results of this project will impact the nation's higher education system and high-tech industries. The ability to pose high-level analytical queries over location based services is needed by knowledge workers in a wide variety of corporations, governments, and security agencies. Parts of this project are being integrated into teaching, which will potentially attract motivated students to pursue doctoral degrees. The research involves developing a suite of algorithms and techniques for understanding the opportunities and challenges of data analytics over location based services. The various data analytics and mining tasks considered include point and path aggregate estimation as well as dual mining over location based services limited by available data access interfaces. The research makes fundamental advancements to engineering by showing how to integrate theoretically-proven algorithms with application-specific details of real-world location based services. A data analytics prototype is also being developed and will be evaluated over several real-world location based services.