Clustering algorithms are widely used methods for organizing data into useful information. The Competitive Agglomeration for Relational Data (CARD) Algorithm is one such clustering algorithm that is designed to organize user sessions into profiles, where each profile would highlight a particular type of user. The CARD algorithm is a viable candidate for Web clustering; however, it does have limitations such as an extended execution time. In addition, the methods that prepare the input data for the CARD algorithm's use employs concepts which seem to be incomplete. These limitations of the CARD algorithm are explored and modifications are introduced to yield a more practical and efficient algorithm.
['Shahram Rahimi', 'Lisa Gandy', 'Bidyut Gupta']
Extracting Web User Profiles Using a Modified CARD Algorithm