human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "coverage of highly cited documents in google scholar web of science and scopus a multidisciplinary comparison"):
  Abstract: Abstract This study explores the extent to which bibliometric indicators based on counts of highly-cited documents could be affected by the choice of data source. The initial hypothesis is that databases that rely on journal selection criteria for their document coverage may not necessarily provide an accurate representation of highly-cited documents across all subject areas, while inclusive databases, which give each document the chance to stand on its own merits, might be better suited to identify highly-cited documents. To test this hypothesis, an analysis of 2515 highly-cited documents published in 2006 that Google Scholar displays in its Classic Papers product is carried out at the level of broad subject categories, checking whether these documents are also covered in Web of Science and Scopus, and whether the citation counts offered by the different sources are similar. The results show that a large fraction of highly-cited documents in the Social Sciences and Humanities (8.6–28.2%) are invisible to Web of Science and Scopus. In the Natural, Life, and Health Sciences the proportion of missing highly-cited documents in Web of Science and Scopus is much lower. Furthermore, in all areas, Spearman correlation coefficients of citation counts in Google Scholar, as compared to Web of Science and Scopus citation counts, are remarkably strong (.83–.99). The main conclusion is that the data about highly-cited documents available in the inclusive database Google Scholar does indeed reveal significant coverage deficiencies in Web of Science and Scopus in several areas of research. Therefore, using these selective databases to compute bibliometric indicators based on counts of highly-cited documents might produce biased assessments in poorly covered areas.

Includes members:
  Member "evidence of open access of scientific publications in google scholar a large scale analysis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "who pays comparing cost sharing models for a gold open access publication environment")
  Member "google scholar as a data source for research assessment":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "google scholar web of science and scopus a systematic comparison of citations in 252 subject categories")
  Member "can we use google scholar to identify highly cited documents":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "author level metrics in the new academic profile platforms the online behaviour of the bibliometrics community")
  Member "the accuracy of confidence intervals for field normalised indicators":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "female citation impact superiority 1996 2018 in six out of seven english speaking nations")
  Member "three practical field normalised alternative indicator formulae for research evaluation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the demise of single authored publications in computer science a citation network analysis")
  Member "a two sided academic landscape portrait of highly cited documents in google scholar 1950 2013":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "challenges of measuring software impact through citations an examination of the lme4 r package")
  Member "the journal coverage of web of science and scopus a comparative analysis":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a tale of two databases the use of web of science and scopus in academic papers")
  Member "methods for estimating the size of google scholar":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "google scholar as a data source for research assessment")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.DL(Digital Libraries)