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 "normalizing the measurement of citation performance principles for comparing sets of documents"):
  Abstract: Using citation analysis, sets of documents can be compared as independent samples; for example, in terms of average citation counts using potentially different reference sets. From this perspective, the size of samples matters only for the identification of significant differences and estimating margins of error. Using the percentile rank approach, differences among citation distributions can be studied non-parametrically and in a single scheme. Comparison among the sets clarifies that the different sizes of samples affect the weighing of the probabilities and therefore the rankings. We distinguish among (1) the normalization of papers against external reference sets, (2) normalization in terms of frequencies relative to the margin-totals of independent versus dependent samples, and (3) the potentially normative definition of percentile rank classes for the evaluation (e.g., top-1% most highly cited, median, etc.). When the sets to be evaluated are considered as subsamples of a single sample, the consequent citation indicator can be negatively correlated to citation indicators used hitherto.

Includes members:
  Member "simple arithmetic versus intuitive understanding the case of the impact factor":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "h index and its alternative a review")
  Member "towards a new crown indicator some theoretical considerations":
    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 "normalization at the field level fractional counting of citations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "creativity in science and the link to cited references is the creative potential of papers reflected in their cited references")
  Member "caveats for the journal and field normalizations in the cwts leiden evaluations of research performance":
    also connected through other hyperedges:
      - Hyperedge HE-4 (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 "how fractional counting affects the impact factor normalization in terms of differences in citation potentials among fields of science":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a review of theory and practice in scientometrics")
  Member "remaining problems with the new crown indicator mncs of the cwts":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "creativity in science and the link to cited references is the creative potential of papers reflected in their cited references")
  Member "rivals for the crown reply to opthof and leydesdorff":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "field normalization of scientometric indicators")
  Member "towards a new crown indicator an empirical analysis":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "impact factor volatility to a single paper a comprehensive analysis")

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)