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: "extension of modularity density for overlapping community structure"
  Abstract: Modularity is widely used to effectively measure the strength of the disjoint community structure found by community detection algorithms. Although several overlapping extensions of modularity were proposed to measure the quality of overlapping community structure, there is lack of systematic comparison of different extensions. To fill this gap, we overview overlapping extensions of modularity to select the best. In addition, we extend the Modularity Density metric to enable its usage for overlapping communities. The experimental results on four real networks using overlapping extensions of modularity, overlapping modularity density, and six other community quality metrics show that the best results are obtained when the product of the belonging coefficients of two nodes is used as the belonging function. Moreover, our experiments indicate that overlapping modularity density is a better measure of the quality of overlapping community structure than other metrics considered.

Connected through hyperedge HE-1 (induced by source paper "a statistical density based analysis of graph clustering algorithm performance"):
  with members:
    - "using synthetic networks for parameter tuning in community detection"
    - "size matters a comparative analysis of community detection algorithms"
    - "graph sketching based massive data clustering"
    - "on the evaluation potential of quality functions in community detection for different contexts"
    - "analysis of network clustering algorithms and cluster quality metrics at scale"
    - "axioms for graph clustering quality functions"
    - "defining and evaluating network communities based on ground truth"
    - "bad communities with high modularity"

Connected through hyperedge HE-2 (induced by source paper "community detection algorithm evaluation with ground truth data"):
  with members:
    - "fuzzy overlapping community quality metrics"
    - "overlapping community detection in networks the state of the art and comparative study"
    - "towards linear time overlapping community detection in social networks"
    - "accuracy measures for the comparison of classifiers"
    - "comparative evaluation of community detection algorithms a topological approach"
    - "defining and evaluating network communities based on ground truth"
    - "a classification for community discovery methods in complex networks"
    - "slpa uncovering overlapping communities in social networks via a speaker listener interaction dynamic process"

Connected through hyperedge HE-3 (induced by source paper "metrics for community analysis a survey"):
  with members:
    - "the ground truth about metadata and community detection in networks"
    - "on the evaluation potential of quality functions in community detection for different contexts"
    - "higher order organization of complex networks"
    - "genperm a unified method for detecting non overlapping and overlapping communities"
    - "z score based modularity for community detection in networks"
    - "permanence and community structure in complex networks"
    - "generalized measures for the evaluation of community detection methods"
    - "generalization of clustering agreements and distances for overlapping clusters and network communities"

Connected through hyperedge HE-4 (induced by source paper "node centric detection of overlapping communities in social networks"):
  with members:
    - "overlapping community detection in networks the state of the art and comparative study"
    - "shaping communities out of triangles"
    - "demon a local first discovery method for overlapping communities"
    - "towards linear time overlapping community detection in social networks"
    - "defining and evaluating network communities based on ground truth"
    - "detect overlapping and hierarchical community structure in networks"
    - "on the np completeness of some graph cluster measures"

Connected through hyperedge HE-5 (induced by source paper "genperm a unified method for detecting non overlapping and overlapping communities"):
  with members:
    - "overlapping community detection in networks the state of the art and comparative study"
    - "towards linear time overlapping community detection in social networks"
    - "community detection using a neighborhood strength driven label propagation algorithm"
    - "detect overlapping and hierarchical community structure in networks"

Connected through hyperedge HE-6 (induced by source paper "fuzzy overlapping community quality metrics"):
  with members:
    - "identifying robust communities and multi community nodes by combining top down and bottom up approaches to clustering"
    - "a new metric for quality of network community structure"
    - "overlapping community detection in networks the state of the art and comparative study"
    - "towards linear time overlapping community detection in social networks"
    - "defining and evaluating network communities based on ground truth"
    - "detect overlapping and hierarchical community structure in networks"

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.SI(Social and Information Networks)