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 "google scholar as a data source for research assessment"):
  Abstract: The launch of Google Scholar (GS) marked the beginning of a revolution in the scientific information market. This search engine, unlike traditional databases, automatically indexes information from the academic web. Its ease of use, together with its wide coverage and fast indexing speed, have made it the first tool most scientists currently turn to when they need to carry out a literature search. Additionally, the fact that its search results were accompanied from the beginning by citation counts, as well as the later development of secondary products which leverage this citation data (such as Google Scholar Metrics and Google Scholar Citations), made many scientists wonder about its potential as a source of data for bibliometric analyses. The goal of this chapter is to lay the foundations for the use of GS as a supplementary source (and in some disciplines, arguably the best alternative) for scientific evaluation. First, we present a general overview of how GS works. Second, we present empirical evidences about its main characteristics (size, coverage, and growth rate). Third, we carry out a systematic analysis of the main limitations this search engine presents as a tool for the evaluation of scientific performance. Lastly, we discuss the main differences between GS and other more traditional bibliographic databases in light of the correlations found between their citation data. We conclude that Google Scholar presents a broader view of the academic world because it has brought to light a great amount of sources that were not previously visible.

Includes members:
  Member "can we use google scholar to identify highly cited documents":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "author level metrics in the new academic profile platforms the online behaviour of the bibliometrics community")
  Member "a two sided academic landscape portrait of highly cited documents in google scholar 1950 2013":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "challenges of measuring software impact through citations an examination of the lme4 r package")
  Member "2016 google scholar metrics released a matter of languages and something else":
    also connected through other hyperedges:
      (none)
  Member "methods for estimating the size of google scholar":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "coverage of highly cited documents in google scholar web of science and scopus a multidisciplinary comparison")
  Member "a new methodology for comparing google scholar and scopus":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "prevalence of potentially predatory publishing in scopus on the country level")
  Member "google scholar metrics 2014 a low cost bibliometric tool":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "implementing recommendation algorithms in a large scale biomedical science knowledge base")
  Member "does google scholar contain all highly cited documents 1950 2013":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "analyzing the disciplinary focus of universities can rankings be a one size fits all")
  Member "h index of scientific nursing journals according to google scholar metrics 2007 2011":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "google scholar the big data bibliographic tool")

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)