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: "bibliometric approximation of a scientific specialty by combining key sources title words authors and references"
  Abstract: Bibliometric methods for the analysis of highly specialized subjects are increasingly investigated and debated. Information and assessments well-focused at the specialty level can help make important decisions in research and innovation policy. This paper presents a novel method to approximate the specialty to which a given publication record belongs. The method partially combines sets of key values for four publication data fields: source, title, authors and references. The approach is founded in concepts defining research disciplines and scholarly communication, and in empirically observed regularities in publication data. The resulting specialty approximation consists of publications associated to the investigated publication record via key values for at least three of the four data fields. This paper describes the method and illustrates it with an application to publication records of individual scientists. The illustration also successfully tests the focus of the specialty approximation in terms of its ability to connect and help identify peers. Potential tracks for further investigation include analyses involving other kinds of specialized publication records, studies for a broader range of specialties, and exploration of the potential for diverse applications in research and research policy context.

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)