Co-clustering for queries and corresponding advertisement - Fan Yang; Bin An; Xizhao Wang (2009 International Conference on Machine Learning and Cybernetics, 2009)
Both documents clustering and words clustering are well studied problems. Most existing algorithms cluster documents (advertisement) and words (query) separately but not simultaneously. In this paper we present a novel idea of analyzing both queries and advertisements which occur with queries at the same time. We present an innovative co-clustering algorithm that suggests queries by co-clustering advertisements and queries. We pose the co-clustering problem as an optimization problem in information theory - the optimal co-clustering maximizes the mutual information between the clustered random variables subject to constraints on the number of row and column clusters.