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: "mapping spatial and temporal changes of global corporate research and development activities by conducting a bibliometric analysis"
  Abstract: Corporate research and development (R&D) activities have long been highly concentrated in a handful of world cities. This is due to the fact that these cities (e.g., Tokyo, New York, London, and Paris) are home to the largest and most powerful transnational corporations and are globally important sites for innovative start-up firms that operate in the fastest growing industries. However, in tandem with the rapid technological changes of our age, corporate R&D activities have shifted towards newly emerging and now globally significant R&D centres, like San Jose, San Francisco, and Boston in the United States, and Beijing, Seoul, and Shenzhen in East Asia. In this paper, I will conduct a bibliometric analysis to define which cities are centres of corporate R&D activities, how different industries influence their performance, and what spatial tendencies characterise the period from 1980 to 2014. The bibliometric analysis is based upon an assumption that implies there is a close connection between the number of scientific articles published by a given firm and the volume of its R&D activity.

Connected through hyperedge HE-1 (induced by source paper "a spatial scientometric analysis of the publication output of cities worldwide"):
  with members:
    - "exploring the position of cities in global corporate research and development a bibliometric analysis by two different geographical approaches"
    - "the journal coverage of web of science and scopus a comparative analysis"
    - "how have the eastern european countries of the former warsaw pact developed since 1990 a bibliometric study"
    - "mapping excellence in the geography of science an approach based on scopus data"
    - "globalisation of science in kilometres"
    - "the detection of hot regions in the geography of science a visualization approach by using density maps"
    - "mapping the geography of science distribution patterns and networks of relations among cities and institutes"

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)