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: "challenges for regional innovation policies in cee countries spatial concentration and foreign control of us patenting"
  Abstract: Using techniques of data collection and mapping as overlays to Google Maps – on the basis of patent information available online at the U.S. Patent and Trademark Office (USPTO) – we point at two major and interconnected challenges that policy-makers face in Central and Eastern Europe (CEE) when combating the lagging innovation performance. First, we address the spatial concentration by using a distribution analysis at the city level. The results suggest that patenting is concentrated in post-socialist territories more than in western nations and regions. However, there is not a single outstanding hub in CEE when one compares USPTO patents normalized for the respective population sizes. Secondly, we argue that dominance of foreign control over USPTO patents is mostly embodied in international co-operations at the individual level, and only rarely spilled-over to MNE subsidiaries. In our opinion, catching-up of CEE in terms of patenting is unlikely, unless innovation policy measures focus on growing hubs and target both domestic inventors and international relations of companies.

Connected through hyperedge HE-1 (induced by source paper "can synergy in triple helix relations be quantified a review of the development of the triple helix indicator"):
  with members:
    - "brics countries and scientific excellence a bibliometric analysis of most frequently cited papers"
    - "knowledge generating efficiency in innovation systems the relation between structural and temporal effects"
    - "the european union china and the united states in the top 1 and top 10 layers of most frequently cited publications competition and collaborations"
    - "measuring triple helix synergy in the russian innovation systems at regional provincial and national levels"
    - "measuring the knowledge based economy of china in terms of synergy among technological organizational and geographic attributes of firms"
    - "redundancy generation in university industry government relations the triple helix modeled measured and simulated"
    - "the triple helix of university industry government relations at the country level and its dynamic evolution under the pressures of globalization"
    - "the swedish system of innovation regional synergies in a knowledge based economy"

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.CY(Computers and Society)