Factor Analysis to Support the Visualization and Interpretation of Clusters of Portal Users
Carmen Rebelo, Pedro Quelhas Brito, Carlos Soares, Alípio Jorge · 2006
Clusterings based on many variables are difficult to visualize and interpret. We present a methodology based on factor analysis (FA) which can be used for that purpose. FA generates a small set of variables which encode most of the information in the original variables. We apply the methodology to segment the users of a Web portal, using access log data. It not only makes it simpler to visualize and understand the clusters which are obtained on the original variables but it also helps the analyst in selecting some of the original variables for further analysis of those clusters