Computing and Storage Infrastructure for Big Data Analytics

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In a world where data are growing at extraordinary rates, there is a huge demand for fast and effective analysis of big data to discover useful information. In the Data Mining Lab at York University, we are working on a number of research projects supported by NSERC for developing effective, efficient, and novel solutions for mining big data. Most of our projects involve industry collaboration where high volumes of data are used to develop solutions to practical problems in industry. This RTI grant will provide computational support required by these projects. We request a data storage server, a big memory server, and a number of workstations. The equipment will be used by the students and postdoctoral fellows working on the projects. These projects include (1) Online mining of big data streams using cloud computing, (2) Semi-supervised learning from data streams with emerging classes, (3) Novel geodesic and contour global optimization and its application to machine learning, (4) Data and visual analytics for decision marking in next generation news media, (5) Application of IBM platform solutions for data analytics problems, (6) An online integrated health risk assessment and recommendation tool, (7) Developing smart conversational systems, (8) Predicting forced migration using big data of news articles, (9) Developing a cloud-based platform for real-time facility analytics, and (10) Graph Mining and Exploration Algorithms. Our research has strong collaborations with Canadian industry, and covers various application areas that are involved with big data. We will develop novel and more effective technological solutions that can turn big data into beneficial actions for business. We believe such applications will result in product enhancements and new products for our partners, and will bring them significant competitive advantages globally.