Abstract
AMiner is a novel online academic search and mining system, and it aims to provide a systematic modeling approach to help researchers and scientists gain a deeper understanding of the large and heterogeneous networks formed by authors, papers, conferences, journals and organizations. The system is subsequently able to extract researchers’ profiles automatically from the Web and integrates them with published papers by a way of a process that first performs name disambiguation. Then a generative probabilistic model is devised to simultaneously model the different entities while providing a topic-level expertise search. In addition, AMiner offers a set of researcher-centered functions, including social influence analysis, relationship mining, collaboration recommendation, similarity analysis, and community evolution. The system has been in operation since 2006 and has been accessed from more than 8 million independent IP addresses residing in more than 200 countries and regions.
Highlights
A variety of academic social networking websites including Google Scholar, Microsoft Academic, Semantic Scholar, ResearchGate and Academia.edu have gained great popularity over the past decade
AMiner is a novel online academic search and mining system, and it aims to provide a systematic modeling approach to help researchers and scientists gain a deeper understanding of the large and heterogeneous networks formed by authors, papers, conferences, journals and organizations
For several features in the system, e.g., profile extraction, name disambiguation, academic topic modeling, expertise search and academic social network mining, we propose some new approaches to overcome the drawbacks that exist in the conventional methods
Summary
A variety of academic social networking websites including Google Scholar , Microsoft Academic , Semantic Scholar , ResearchGate and Academia.edu have gained great popularity over the past decade. The common purpose of these academic social networking systems is to provide researchers with an integrated platform to query academic information and resources, share their own achievements, and connect with other researchers. Several issues within academic social networks have been investigated in these systems. Most of the issues are investigated separately through independent processes. There is not a congruent process or series of methods for mining the whole of disparate academic social networks. The lack of such methods can be attributed to two reasons:
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