Choosing Attribute Weights for Item Dissimilarity using Clikstream Data with an Application to a Product Catalog Map

Martijn Kagie (), Michiel van Wezel and Patrick Groenen ()

ERIM Report Series Research in Management from Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam

Abstract: In content- and knowledge-based recommender systems often a measure of (dis)similarity between items is used. Frequently, this measure is based on the attributes of the items. However, which attributes are important for the users of the system remains an important question to answer. In this paper, we present an approach to determine attribute weights in a dissimilarity measure using clickstream data of an e-commerce website. Counted is how many times products are sold and based on this a Poisson regression model is estimated. Estimates of this model are then used to determine the attribute weights in the dissimilarity measure. We show an application of this approach on a product catalog of MP3 players provided by Compare Group, owner of the Dutch price comparison site http://www.vergelijk.nl, and show how the dissimilarity measure can be used to improve 2D product catalog visualizations.

Keywords: attribute weights; clickstream data; comparison; dissimilarity measure (search for similar items in EconPapers)
JEL-codes: C44 C53 D8 M M31 (search for similar items in EconPapers)
Date: 2008-04-25
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Citations: View citations in EconPapers (3)

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