Mining Diversity on Networks

Abstract. Despite the recent emergence of many large-scale networks in different application domains, an important measure that captures a participant’s diversity in the network has been largely neglected in previous studies. Namely, diversity characterizes how diverse a given node connects with its peers. In this paper, we give a comprehensive study of this concept. We first lay out two criteria that capture the semantic meaning of diversity, and then propose a compliant definition which is simple enough to embed the idea. An efficient top-k diversity ranking algorithm is developed for computation on dynamic networks. Experiments on both synthetic and real datasets give interesting results, where individual nodes identified with high diversities are intuitive.

• Type: Conference
• Year: 2010
• Where: DASFAA
• Authors: Lu Liu, Feida Zhu, Chen Chen, Xifeng Yan, Jiawei Han, Philip S. Yu, Shiqiang Yang
• Keywords: DASFAA 2010, Database, Diversity Ranking Algorithm, Large-scale Networks, Participant’s Diversity