Adding Personality to Information Clustering

This article presents a new information management method called user-con gurable clustering that integrates the exibility of clustering systems in handling novel data and the ease of use of categorization systems in providing structure. Based on a predictive self-organizing network that performs synchronized clustering of information and preference vectors, we illustrate how a user can in uence the clustering of information vectors by encoding his/her preferences as preference vectors. We present algorithms for performing the various cluster personalization functions including labeling, adding, deleting, merging, and splitting of information clusters. User-con gurable clustering has been incorporated into a web-based competitive intelligence system known as Flexible Organizer for Competitive Intelligence (FOCI). We illustrate a sample session of FOCI which shows how a user may create and personalize an information portfolio according to his/her preferences and how the system discovers novel information groupings while organizing familiar information according to user-de ned themes.