Extraction and mining of an academic social network

This paper addresses several key issues in extraction and mining of an academic social network: 1) extraction of a researcher social network from the existing Web; 2) integration of the publications from existing digital libraries; 3) expertise search on a given topic; and 4) association search between researchers. We developed a social network system, called ArnetMiner, based on proposed methods to the above problems. In total, 448,470 researcher profiles and 981,599 publications were extracted/integrated after the system having been in operation for two years. The paper describes the architecture and main features of the system. It also briefly presents the experimental results of the proposed methods. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval, Digital Libraries, I.2.6 [Artificial Intelligence]: Learning, H.2.8 [Database Management]: Database Applications. General Terms Algorithms, Experimentation Keywords Social N...

• Type: Conference
• Year: 2008
• Where: WWW
• Authors: Jie Tang, Jing Zhang, Limin Yao, Juan-Zi Li
• Keywords: Internet Technology, Researcher Social Network, Social Network, Social Network System, WWW 2008