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: "overlapping community detection in networks the state of the art and comparative study"
  Abstract: This article reviews the state-of-the-art in overlapping community detection algorithms, quality measures, and benchmarks. A thorough comparison of different algorithms (a total of fourteen) is provided. In addition to community-level evaluation, we propose a framework for evaluating algorithms' ability to detect overlapping nodes, which helps to assess overdetection and underdetection. After considering community-level detection performance measured by normalized mutual information, the Omega index, and node-level detection performance measured by F-score, we reached the following conclusions. For low overlapping density networks, SLPA, OSLOM, Game, and COPRA offer better performance than the other tested algorithms. For networks with high overlapping density and high overlapping diversity, both SLPA and Game provide relatively stable performance. However, test results also suggest that the detection in such networks is still not yet fully resolved. A common feature observed by various algorithms in real-world networks is the relatively small fraction of overlapping nodes (typically less than 30p), each of which belongs to only 2 or 3 communities.

Connected through hyperedge HE-1 (induced by source paper "meta learning with relational information for short sequences"):
  with members:
    - "on first order meta learning algorithms"
    - "recasting gradient based meta learning as hierarchical bayes"
    - "reptile a scalable metalearning algorithm"
    - "probabilistic model agnostic meta learning"
    - "motifs in temporal networks"
    - "prototypical networks for few shot learning"
    - "fake news mitigation via point process based intervention"
    - "a dirichlet mixture model of hawkes processes for event sequence clustering"

Connected through hyperedge HE-2 (induced by source paper "self falsifiable hierarchical detection of overlapping communities on social networks"):
  with members:
    - "gemsec graph embedding with self clustering"
    - "hidden community detection in social networks"
    - "the ground truth about metadata and community detection in networks"
    - "community detection in networks with unequal groups"
    - "spectral redemption in clustering sparse networks"
    - "demon a local first discovery method for overlapping communities"
    - "percolation computation in complex networks"
    - "defining and evaluating network communities based on ground truth"

Connected through hyperedge HE-3 (induced by source paper "communitygan community detection with generative adversarial nets"):
  with members:
    - "adversarial network embedding"
    - "seqgan sequence generative adversarial nets with policy gradient"
    - "node2vec scalable feature learning for networks"
    - "semi supervised classification with graph convolutional networks"
    - "gradient estimation using stochastic computation graphs"
    - "line large scale information network embedding"
    - "deepwalk online learning of social representations"
    - "using triangles to improve community detection in directed networks"

Connected through hyperedge HE-4 (induced by source paper "discovering communities of community discovery"):
  with members:
    - "a survey of community search over big graphs"
    - "community structure a comparative evaluation of community detection methods"
    - "community discovery in dynamic networks a survey"
    - "labelrank a stabilized label propagation algorithm for community detection in networks"
    - "clustering and community detection in directed networks a survey"
    - "demon a local first discovery method for overlapping communities"
    - "a classification for community discovery methods in complex networks"
    - "community detection via semi synchronous label propagation algorithms"

Connected through hyperedge HE-5 (induced by source paper "structure preserving community in a multilayer network definition detection and analysis"):
  with members:
    - "generic multilayer network data analysis with the fusion of content and structure"
    - "community extraction in multilayer networks with heterogeneous community structure"
    - "modularity in complex multilayer networks with multiple aspects a static perspective"
    - "organizational chart inference"
    - "a survey of heterogeneous information network analysis"
    - "querying knowledge graphs by example entity tuples"
    - "mining attribute structure correlated patterns in large attributed graphs"
    - "clustering with multi layer graphs a spectral perspective"

Connected through hyperedge HE-6 (induced by source paper "daoc stable clustering of large networks"):
  with members:
    - "bridging the gap between community and node representations graph embedding via community detection"
    - "accuracy evaluation of overlapping and multi resolution clustering algorithms on large datasets"
    - "consensus community detection in multilayer networks using parameter free graph pruning"
    - "clubmark a parallel isolation framework for benchmarking and profiling clustering algorithms on numa architectures"
    - "equivalence between modularity optimization and maximum likelihood methods for community detection"
    - "fuzzy overlapping community quality metrics"
    - "defining and evaluating network communities based on ground truth"
    - "slpa uncovering overlapping communities in social networks via a speaker listener interaction dynamic process"

Connected through hyperedge HE-7 (induced by source paper "efficient community detection in boolean composed multiplex networks"):
  with members:
    - "community detection link prediction and layer interdependence in multilayer networks"
    - "modularity in complex multilayer networks with multiple aspects a static perspective"
    - "generalized measures for the evaluation of community detection methods"
    - "networkit an interactive tool suite for high performance network analysis"
    - "mining attribute structure correlated patterns in large attributed graphs"
    - "clustering with multi layer graphs a spectral perspective"

Connected through hyperedge HE-8 (induced by source paper "an efficient framework for computing structure and semantics preserving community in a heterogeneous multilayer network"):
  with members:
    - "community extraction in multilayer networks with heterogeneous community structure"
    - "organizational chart inference"
    - "a survey of heterogeneous information network analysis"
    - "community structure in large networks natural cluster sizes and the absence of large well defined clusters"

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)