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.
|Titolo:||User profiling with hierarchical context: An e-retailer case study|
|Data di pubblicazione:||2007|
|Nome del convegno:||6th International and Interdisciplinary Conference, CONTEXT 2007|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1007/978-3-540-74255-5_28|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|