Improving Efficiency of Link Clustering on Multi-Core Machines
Guanhua Yan
Binghamton University

Link clustering groups different edges in a graph according to their similarities. Link clustering can reveal the overlapping and hierarchical organizations in a wide spectrum of networks. This work studies how to improve efficiency of link clustering along three dimensions, algorithm, modeling, and parallelization, on multi-core machines. We evaluate the efficiency improved due to each of the three dimensions using word association graphs extracted from a twitter dataset.