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: "folksodriven structure network"
  Abstract: Nowadays folksonomy is used as a system derived from user-generated electronic tags or keywords that annotate and describe online content. But it is not a classification system as an ontology. To consider it as a classification system it would be necessary to share a representation of contexts by all the users. This paper is proposing the use of folksonomies and network theory to devise a new concept: a "Folksodriven Structure Network" to represent folksonomies. This paper proposed and analyzed the network structure of Folksodriven tags thought as folsksonomy tags suggestions for the user on a dataset built on chosen websites. It is observed that the Folksodriven Network has relative low path lengths checking it with classic networking measures (clustering coefficient). Experiment result shows it can facilitate serendipitous discovery of content among users. Neat examples and clear formulas can show how a "Folksodriven Structure Network" can be used to tackle ontology mapping challenges.

Connected through hyperedge HE-1 (induced by source paper "emergent behaviors from folksonomy driven interactions"):
  with members:
    - "automatic data deformation analysis on evolving folksonomy driven environment"
    - "function of forgetfulness for the tedium of oblivion on liquidity of ontology matching"
    - "liquidity on web dynamic network"
    - "elasticity on ontology matching of folksodriven structure network"
    - "faceted semantic search for personalized social search"
    - "cluster analysis for a scale free folksodriven structure network"
    - "search for hidden knowledge in collective intelligence dealing indeterminacy ontology of folksonomy with linguistic pragmatics and quantum logic"
    - "ontology temporal evolution for multi entity bayesian networks under exogenous and endogenous semantic updating"

Connected through hyperedge HE-2 (induced by source paper "function of forgetfulness for the tedium of oblivion on liquidity of ontology matching"):
  with members:
    - "elasticity on ontology matching of folksodriven structure network"
    - "intelligent interface architectures for folksonomy driven structure network"

Connected through hyperedge HE-3 (induced by source paper "liquidity on web dynamic network"):
  with members:
    - "elasticity on ontology matching of folksodriven structure network"
    - "intelligent interface architectures for folksonomy driven structure network"

Connected through hyperedge HE-4 (induced by source paper "elasticity on ontology matching of folksodriven structure network"):
  with members:
    - "cluster analysis for a scale free folksodriven structure network"
    - "ontology temporal evolution for multi entity bayesian networks under exogenous and endogenous semantic updating"

Connected through hyperedge HE-5 (induced by source paper "cluster analysis for a scale free folksodriven structure network"):
  with members:
    - "folks in folksonomies social link prediction from shared metadata"
    - "ontology temporal evolution for multi entity bayesian networks under exogenous and endogenous semantic updating"
    - "the structure of collaborative tagging systems"
    - "folksonomy as a complex network"

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.IR(Information Retrieval)