Co-clustering for queries and corresponding advertisement
Fan Yang, Bin An, Xizhao Wang · 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.