Infrastructures, methods, and tools for mining and analyzing personal behavior for innovative recommender and learning systems using hardware accelerators

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The long-term objective of our research program is to develop, establish, and disseminate advanced infrastructures, methods, and tools to support behavior mining and analysis for innovative applications including (i) web recommender systems; (ii) computer aided sports instruction systems; and (iii) remote physical therapy and rehabilitation systems. In particular, we will (1) investigate theories, methods, and techniques for capturing, mining, tracking, modeling, representing, classifying, and archiving personal behavior; (2) implement the resulting methods and techniques in practical applications using embedded devices; and (3) optimize these applications and devices using programmable and configurable hardware such as FPGAs, netFPGAs, and BEE3/4. Computer aided sports instruction is an attractive alternative to the human coaching approach, with considerable savings in space, time, and cost. We are designing a novel tennis e-learning system using a game controller as a virtual racquet to provide learners skill improvement recommendations. Our hypothesis is that the results from this e-learning system can be readily applied to rehabilitation and in particular remote physical therapy. A patient then simply follows the prescribed motions and personalized recommendation at home without the need to visit a clinic. Thus, the methodology involves (a) developing theories of and methods for behavior analysis, (b) developing efficient algorithms and techniques to manipulate behavior knowledge, (c) optimizing the implementation using hardware accelerators, (d) evaluating these techniques using practical applications, and iterating over these four phases. This research is timely and a great training ground for HQP. Investigating personal behavior knowledge is not only a foundation for the applications targeted by our research program but also a foundation for recommender and e-learning systems in general. Our target applications have great potential to be turned into products by our industrial partners.