AMiner: Search and Mining of Academic Social Networks
Huaiyu Wan1; Yutao Zhang2; Jing Zhang3; Jie Tang2
Source PublicationData Intelligence

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.

KeywordAcademic Social Networks Profile Extraction Name Disambiguation Topic Modeling Expertise Search Network Mining
MOST Discipline Catalogue管理学::图书情报与档案管理
Indexed By其他
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Document Type期刊论文
Corresponding AuthorJie Tang
Affiliation1.School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
2.Information School, Renmin University of China, Beijing 100872, China
3.Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
First Author Affilication中国科学院文献情报中心
Corresponding Author Affilication中国科学院文献情报中心
Recommended Citation
GB/T 7714
Huaiyu Wan,Yutao Zhang,Jing Zhang,et al. AMiner: Search and Mining of Academic Social Networks[J]. Data Intelligence,2019,1(1):58-76.
APA Huaiyu Wan,Yutao Zhang,Jing Zhang,&Jie Tang.(2019).AMiner: Search and Mining of Academic Social Networks.Data Intelligence,1(1),58-76.
MLA Huaiyu Wan,et al."AMiner: Search and Mining of Academic Social Networks".Data Intelligence 1.1(2019):58-76.
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