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 "evaluating journal quality a review of journal citation indicators and ranking in business and management"):
  Abstract: Evaluating the quality of academic journal is becoming increasing important within the context of research performance evaluation. Traditionally, journals have been ranked by peer review lists such as that of the Association of Business Schools (UK) or though their journal impact factor (JIF). However, several new indicators have been developed, such as the h-index, SJR, SNIP and the Eigenfactor which take into account different factors and therefore have their own particular biases. In this paper we evaluate these metrics both theoretically and also through an empirical study of a large set of business and management journals. We show that even though the indicators appear highly correlated in fact they lead to large differences in journal rankings. We contextualize our results in terms of the UK's large scale research assessment exercise (the RAE/REF) and particularly the ABS journal ranking list. We conclude that no one indicator is superior but that the h-index (which includes the productivity of a journal) and SNIP (which aims to normalize for field effects) may be the most effective at the moment.

Includes members:
  Member "a review of theory and practice in scientometrics":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data")
  Member "comprehensive indicator comparisons intelligible to non experts the case of two snip versions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a review of the literature on citation impact indicators")
  Member "identifying research fields within business and management a journal cross citation analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a review of theory and practice in scientometrics")
  Member "a review of the literature on citation impact indicators":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data")
  Member "aggregated journal journal citation relations in scopus and web of science matched and compared in terms of networks maps and interactive overlays":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "discontinuities in citation relations among journals self organized criticality as a model of scientific revolutions and change")
  Member "methods for the generation of normalized citation impact scores in bibliometrics which method best reflects the judgements of experts":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an evaluation of percentile measures of citation impact and a proposal for making them better")
  Member "the operationalization of fields as wos subject categories wcs in evaluative bibliometrics the cases of library and information science and science technology studies":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "practical method to reclassify web of science articles into unique subject categories and broad disciplines")
  Member "a systematic empirical comparison of different approaches for normalizing citation impact indicators":
    also connected through other hyperedges:
      - Hyperedge HE-8 (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")

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)