Maximal Clique Summarization

Maximal clique has a broad range of applications, e.g., community detection, bioinformatics, anomaly detection and graph visualization. However, the sheer number of maximal cliques brings the challenge to fully examine all the maximal cliques. In addition, the omnipresent overlaps between cliques imply that it may not be necessary to process every maximal clique. As a result, finding a summary for all maximal cliques is deemed important in information distribution, influence estimation, cost-effective marketing, etc. In this thesis, we study how to find a representative yet concise summary for maximal cliques.