In this paper, we present a system based on an appropriately targeted version of the well-known fuzzy C-means (FCM) algorithm to determine a small number of profiles of typical Web site users from the Web access log. These profiles can be extremely useful, for instance, to customize the Web site, or to send personalized advertisements. After filtering the access log, for instance, by eliminating occasional users, the FCM algorithm clusters the users of the Web site into groups characterized by a set of common interests and represented by a prototype, which defines the profile of the group typical member. To show the effectiveness of our system, we describe how the profiles determined by the FCM algorithm are a concise representation of the association rules discovered applying the well-known A-priori algorithm to the raw access log data
A system based on a modified version of the FCM algorithm for profiling Web users from access log
CORSINI, PAOLO;LAZZERINI, BEATRICE;MARCELLONI, FRANCESCO
2003-01-01
Abstract
In this paper, we present a system based on an appropriately targeted version of the well-known fuzzy C-means (FCM) algorithm to determine a small number of profiles of typical Web site users from the Web access log. These profiles can be extremely useful, for instance, to customize the Web site, or to send personalized advertisements. After filtering the access log, for instance, by eliminating occasional users, the FCM algorithm clusters the users of the Web site into groups characterized by a set of common interests and represented by a prototype, which defines the profile of the group typical member. To show the effectiveness of our system, we describe how the profiles determined by the FCM algorithm are a concise representation of the association rules discovered applying the well-known A-priori algorithm to the raw access log dataI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
