Clustering of bipartite advertiser-keyword graph

In this paper we present top-down and bottom-up hierarchical clustering methods for large bipartite graphs. The top down approach employs a flow-based graph partitioning method, while the bottom up approach is a multiround hybrid of the single-link and average-link agglomerative clustering methods. We evaluate the quality of clusters obtained by these two methods using additional textual information and compare the results against other clustering techniques.