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 "the source normalized impact per paper snip is a valid and sophisticated indicator of journal citation impact"):
  Abstract: This paper is a reply to the article "Scopus's Source Normalized Impact per Paper (SNIP) versus a Journal Impact Factor based on Fractional Counting of Citations", published by Loet Leydesdorff and Tobias Opthof (arXiv:1004.3580v2 [cs.DL]). It clarifies the relationship between SNIP and Elsevier's Scopus. Since Leydesdorff and Opthof's description of SNIP is not complete, it indicates four key differences between SNIP and the indicator proposed by the two authors, and argues why the former is more valid than the latter. Nevertheless, the idea of fractional citation counting deserves further exploration. The paper discusses difficulties that arise if one attempts to apply this principle at the level of individual (citing) papers.

Includes members:
  Member "scopus s source normalized impact per paper snip versus a journal impact factor based on fractional counting of citations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "field normalization of scientometric indicators")
  Member "measuring contextual citation impact of scientific journals":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "how well does i3 perform for impact measurement compared to other bibliometric indicators the convergent validity of several field normalized indicators")
  Member "the sjr indicator a new indicator of journals scientific prestige":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "individual bibliometric assessment university of vienna from numbers to multidimensional profiles")

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)