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 "a systematic empirical comparison of different approaches for normalizing citation impact indicators"):
  Abstract: We address the question how citation-based bibliometric indicators can best be normalized to ensure fair comparisons between publications from different scientific fields and different years. In a systematic large-scale empirical analysis, we compare a traditional normalization approach based on a field classification system with three source normalization approaches. We pay special attention to the selection of the publications included in the analysis. Publications in national scientific journals, popular scientific magazines, and trade magazines are not included. Unlike earlier studies, we use algorithmically constructed classification systems to evaluate the different normalization approaches. Our analysis shows that a source normalization approach based on the recently introduced idea of fractional citation counting does not perform well. Two other source normalization approaches generally outperform the classification-system-based normalization approach that we study. Our analysis therefore offers considerable support for the use of source-normalized bibliometric indicators.

Includes members:
  Member "citation analysis may severely underestimate the impact of clinical research as compared to basic research":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "should citations be field normalized in evaluative bibliometrics an empirical analysis based on propensity score matching")
  Member "on the calculation of percentile based bibliometric indicators":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an evaluation of percentile measures of citation impact and a proposal for making them better")
  Member "source normalized indicators of citation impact an overview of different approaches and an empirical comparison":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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 "field normalized impact factors a comparison of rescaling versus fractionally counted ifs":
    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 "a new methodology for constructing a publication level classification system of science":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "practical method to reclassify web of science articles into unique subject categories and broad disciplines")
  Member "revisiting the scaling of citations for research assessment":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a nation s foreign and domestic professors which have better research performance the italian case")
  Member "how can journal impact factors be normalized across fields of science an assessment in terms of percentile ranks and fractional counts":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "field normalization of scientometric indicators")
  Member "some modifications to the snip journal impact indicator":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "prevalence of potentially predatory publishing in scopus on the country level")

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)