期刊
SCIENTOMETRICS
卷 108, 期 1, 页码 183-200出版社
SPRINGER
DOI: 10.1007/s11192-016-1950-1
关键词
Citation analysis; Bibliometrics; Big data; Machine learning
资金
- National Science Foundation [CNS-0958379, CNS-0855217, ACI-1126113]
- City University of New York High Performance Computing Center at the College of Staten Island
Definitions for influence in bibliometrics are surveyed and expanded upon in this work. On data composed of the union of DBLP and CiteSeer (x) , approximately 6 million publications, a relatively small number of features are developed to describe the set, including loyalty and community longevity, two novel features. These features are successfully used to predict the influential set of papers in a series of machine learning experiments. The most predictive features are highlighted and discussed.
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