Adding Personality to Information Clustering

Abstract

This article presents a new information management method called user-configurable clustering that integrates the flexibility 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, a user can influence the clustering of information vectors by encoding his/her preferences as preference vectors. We illustrate a sample session to show 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-defined themes.