Mining Research Communities in Bibliographical Data

Abstract. Extracting information from very large collections of structured, semistructured or even unstructured data can be a considerable challenge when much of the hidden information is implicit within relationships among entities in the data. Social networks are such data collections in which relationships play a vital role in the knowledge these networks can convey. A bibliographic database is an essential tool for the research community, yet finding and making use of relationships comprised within such a social network is difficult. In this paper we introduce DBconnect, a prototype that exploits the social network coded within the DBLP database by drawing on a new random walk approach to reveal interesting knowledge about the research community and even recommend collaborations.

• Type: Conference
• Year: 2007
• Where: KDD
• Authors: Osmar R. Zaïane, Jiyang Chen, Randy Goebel
• Keywords: Data Mining, KDD 2007, Random Walk Approach, Social Network, Social Networks