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: "a principled methodology for comparing relatedness measures for clustering publications"
  Abstract: There are many different relatedness measures, based for instance on citation relations or textual similarity, that can be used to cluster scientific publications. We propose a principled methodology for evaluating the accuracy of clustering solutions obtained using these relatedness measures. We formally show that the proposed methodology has an important consistency property. The empirical analyses that we present are based on publications in the fields of cell biology, condensed matter physics, and economics. Using the BM25 text-based relatedness measure as evaluation criterion, we find that bibliographic coupling relations yield more accurate clustering solutions than direct citation relations and co-citation relations. The so-called extended direct citation approach performs similarly to or slightly better than bibliographic coupling in terms of the accuracy of the resulting clustering solutions. The other way around, using a citation-based relatedness measure as evaluation criterion, BM25 turns out to yield more accurate clustering solutions than other text-based relatedness measures.

Connected through hyperedge HE-1 (induced by source paper "practical method to reclassify web of science articles into unique subject categories and broad disciplines"):
  with members:
    - "granularity of algorithmically constructed publication level classifications of research publications identification of topics"
    - "algorithmically generated subject categories based on citation relations an empirical micro study using papers on overall water splitting"
    - "which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge"
    - "clustering scientific publications based on citation relations a systematic comparison of different methods"
    - "large scale analysis of the accuracy of the journal classification systems of web of science and scopus"
    - "the operationalization of fields as wos subject categories wcs in evaluative bibliometrics the cases of library and information science and science technology studies"
    - "a new methodology for constructing a publication level classification system of science"

Connected through hyperedge HE-2 (induced by source paper "granularity of algorithmically constructed publication level classifications of research publications identification of topics"):
  with members:
    - "which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge"
    - "generating clustered journal maps an automated system for hierarchical classification"
    - "clustering scientific publications based on citation relations a systematic comparison of different methods"
    - "highly cited papers in library and information science lis authors institutions and network structures"
    - "source normalized indicators of citation impact an overview of different approaches and an empirical comparison"
    - "a new methodology for constructing a publication level classification system of science"
    - "some modifications to the snip journal impact indicator"
    - "can scientific journals be classified in terms of aggregated journal journal citation relations using the journal citation reports"

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)