2019/08/26 by Serge Richard, Richard, Serge, Qiwen Sun +1
Computer Science · Mathematics · #62P99 #Applications (stat.AP) #Data Mining Algorithms and Applications #Data Stream Mining Techniques #Digital Libraries (cs.DL) #FOS: Computer and information sciences #FOS: Mathematics #History and Overview (math.HO) #Machine Learning and Data Classification #cs.DL #math.HO #msc:62P99 #stat.AP
paper · pdf · doi:10.48550/arxiv.1908.10282
arxiv created 2019/08/26 · openalex publication_date 2019/08/26 · arxiv updated 2019/08/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper we initiate some investigations on MathSciNet database. For many mathematicians this website is used on a regular basis, but surprisingly except for the information provided by MathSciNet itself, there exist almost no independent investigations or independent statistics on this database. This current research has been triggered by a rumor: do international collaborations increase the number of citations of an academic work in mathematics? We use MathSciNet for providing some information about this rumor, and more generally pave the way for further investigations on or with MathSciNet. Keywords: MathSciNet, tree-based methods, international collaborations