Mining Diversity on Networks
Conference Proceeding Article
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.
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
Database Systems for Advanced Applications: 15th International Conference, DASFAA 2010, Tsukuba, Japan, April 1-4, 2010, Proceedings, Part I
City or Country
LU, LIU; ZHU, Feida; CHEN, CHEN; YAN, Xifeng; Han, Jiawei; YU, Philip; and YANG, Shiqiang.
Mining Diversity on Networks. (2010). Database Systems for Advanced Applications: 15th International Conference, DASFAA 2010, Tsukuba, Japan, April 1-4, 2010, Proceedings, Part I. 5981, 384-398. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/509