Andrei Broder, Ravi Kumar, et al.
Computer Networks
We describe a novel approach for clustering collections of sets, and its application to the analysis and mining of categorical data. By "categorical data," we mean tables with fields that cannot be naturally ordered by a metric - e.g., the names of producers of automobiles, or the names of products offered by a manufacturer. Our approach is based on an iterative method for assigning and propagating weights on the categorical values in a table; this facilitates a type of similarity measure arising from the co-occurrence of values in the dataset. Our techniques can be studied analytically in terms of certain types of non-linear dynamical systems.
Andrei Broder, Ravi Kumar, et al.
Computer Networks
Alok Aggarwal, Jon Kleinberg, et al.
SIAM Journal on Computing
Paul Beame, Allan Borodin, et al.
SIAM Journal on Computing
Anirban Dasgupta, Prabhakar Raghavan, et al.
KDD 2005