AMiner

Jie Tang
2016 Proceedings of the Ninth ACM International Conference on Web Search and Data Mining - WSDM '16  
In this talk, I present a novel academic search and mining system, AMiner 1 , the second generation of the ArnetMiner system [9] . Different from traditional academic search systems that focus on document (paper) search, AMiner aims to provide a systematic modeling approach to gain a deep understanding of the large and heterogeneous networks formed by authors, papers they have published, and venues in which they were published. The system extracts researchers' profiles automatically from the
more » ... [7] and integrates them with published papers after name disambiguation [3] . It has collected a large scholar dataset, with more than 130,000,000 researcher profiles and 100,000,000 papers from multiple publication databases. We have also developed an approach named COS-NET [12] to connect AMiner with several professional social networks, such as LinkedIn and VideoLectures, which significantly enriches the scholar metadata. Based on our integrated big scholar data, we devised a unified topic modeling approach to modeling the different entities (authors, papers, venues) simultaneously and providing a topic-level expertise search by leveraging the modeling results [8] . In addition, AMiner offers a set of researcher-centered functions, including social influence analysis [5] , influence visualization [1], collaboration recommendation [6], relationship mining [4, 10], similarity analysis [11] , and community evolution [2]. The system has been in operation since 2006 and has attracted more than 7,000,000 independent IP accesses from over 200 countries/regions.
doi:10.1145/2835776.2835849 dblp:conf/wsdm/Tang16 fatcat:2yhy7dxdszhy7px576mm3winxa