human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "validity of basing authors publication strategy on journal impact factors"
  Abstract: Choosing the best scientific venue for the submission of a manuscript, with the aim of maximizing the impact of the future publication, is a frequent task faced by scholars. In this paper, we show that the Impact Factor (IF) of a journal allows to rationally achieve this goal. We take advantage of a comprehensive bibliographic and citation dataset of about 2.5 million articles from 16,000 journals, and demonstrate that the probability of receiving more citations in one journal compared to another is a universal function of the IF values of the two journals. The relation is well described by a modified logistic function, and provides an easy-to-use rule to guide a publication strategy. The benefit of publishing in a journal with a higher IF value, instead of another with a lower one grows slowly as a function of the ratio of their IF values. For example, receiving more citations is granted in 90\% of the cases only if the IF ratio is greater than $\sim$6, while targeting a journal with an IF 2$\times$ higher than another brings in marginal citation benefit.

Connected through hyperedge HE-1 (induced by source paper "should citations be field normalized in evaluative bibliometrics an empirical analysis based on propensity score matching"):
  with members:
    - "the preeminence of ethnic diversity in scientific collaboration"
    - "the geography of references in elite articles which countries contribute to the archives of knowledge"
    - "field normalization of scientometric indicators"
    - "which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge"
    - "relative citation ratio rcr an empirical attempt to study a new field normalized bibliometric indicator"
    - "a review of theory and practice in scientometrics"
    - "large scale analysis of the accuracy of the journal classification systems of web of science and scopus"
    - "a review of the literature on citation impact indicators"

Connected through hyperedge HE-2 (induced by source paper "skewness of citation impact data and covariates of citation distributions a large scale empirical analysis based on web of science data"):
  with members:
    - "methods for the generation of normalized citation impact scores in bibliometrics which method best reflects the judgements of experts"
    - "the weakening relationship between the impact factor and papers citations in the digital age"
    - "the use of percentiles and percentile rank classes in the analysis of bibliometric data opportunities and limits"
    - "the structure of the arts humanities citation index a mapping on the basis of aggregated citations among 1 157 journals"
    - "caveats for the journal and field normalizations in the cwts leiden evaluations of research performance"

Question: Please tell me which class the center node 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)