User Profiling with Hierarchical Context: An e-Retailer Case Study

In e-commerce applications, no systematic research has been provided to evaluate if the use of a detailed and rich contextual representation improves the user modeling predictive performances. An underestimated issue is also evaluating if context could be inferred by existing customer data off-line, in spite of getting the customer involved on-line in the gathering process. In this paper, we address those problems, defining context as “the intent of” a customer purchase. To this aim, we collected data containing rich contextual information, hierarchically structured, by developing a special-purpose browser. The experimental results show that the finer the granularity of contextual information the better is the modeling of customers’ behavior. Representing the context in a hierarchical structure is a necessary condition, for inferring the context off-line, but it’s not a sufficient one.

• Type: Conference
• Year: 2007
• Where: CONTEXT
• Authors: Cosimo Palmisano, Alexander Tuzhilin, Michele Gorgoglione
• Keywords: CONTEXT 2007, Contextual Information, Customer Data Off-line, Information Management, Rich Contextual Representation