Situation-aware predictive ecommerce market analytics

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We propose to develop a new research partnership between Terapeak of Victoria and researchers at University of Victoria. The mission of Terapeak is to analyze, understand, and predict consumer and product behaviour in e-commerce markets such as eBay. The aim of the project is to optimize the processes of selling products in an e-commerce setting by adding predictive analytics and collaborative filtering based on statistical techniques and economic models. We will develop services to generate advice on how to customize an order to sell a particular product. In particular, we will create new software tools to create such advice based on two specific data sets: (1) the transactions for a given type of product in a given time interval; and (2) the attributes of ranked lists of merchants (e.g., best and worst selling merchants). These special data sets are available through our industrial partner Terapeak, who has an agreement with eBay to commercialize such data. This project will solve a well-defined, company-specific problem, and generate new knowledge in the form of innovative predictive analytics and collaborative filtering techniques for selected e-commerce platforms. The University of Victoria researchers have extensive experience in algorithms, optimization, smarter commerce, data mining, and self-adaptive systems to conduct this six-month project focusing on specific short-term objectives that address a specific research challenge of Terapeak. The university researchers will work closely with Terapeak developers to ensure effective technology transfer. One of the major goals of Terapeak is to expand their offerings of advice-based services; thus, this project is of strategic importance to the industrial partner. This project is expected to result in significant economic benefit to this Victoria company, as well as British