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: "leveraging disjoint communities for detecting overlapping community structure"
  Abstract: Network communities represent mesoscopic structure for understanding the organization of real-world networks, where nodes often belong to multiple communities and form overlapping community structure in the network. Due to non-triviality in finding the exact boundary of such overlapping communities, this problem has become challenging, and therefore huge effort has been devoted to detect overlapping communities from the network.In this paper, we present PVOC (Permanence based Vertex-replication algorithm for Overlapping Community detection), a two-stage framework to detect overlapping community structure. We build on a novel observation that non-overlapping community structure detected by a standard disjoint community detection algorithm from a network has high resemblance with its actual overlapping community structure, except the overlapping part. Based on this observation, we posit that there is perhaps no need of building yet another overlapping community finding algorithm; but one can efficiently manipulate the output of any existing disjoint community finding algorithm to obtain the required overlapping structure. We propose a new post-processing technique that by combining with any existing disjoint community detection algorithm, can suitably process each vertex using a new vertex-based metric, called permanence, and thereby finds out overlapping candidates with their community memberships. Experimental results on both synthetic and large real-world networks show that PVOC significantly outperforms six state-of-the-art overlapping community detection algorithms in terms of high similarity of the output with the ground-truth structure. Thus our framework not only finds meaningful overlapping communities from the network, but also allows us to put an end to the constant effort of building yet another overlapping community detection algorithm.

Connected through hyperedge HE-1 (induced by source paper "ensemble based overlapping community detection using disjoint community structures"):
  with members:
    - "dyperm maximizing permanence for dynamic community detection"
    - "iedc an integrated approach for overlapping and non overlapping community detection"
    - "ensemble based algorithms to detect disjoint and overlapping communities in networks"
    - "metrics for community analysis a survey"
    - "think locally act locally detection of small medium sized and large communities in large networks"
    - "on the formation of circles in co authorship networks"
    - "overlapping community detection in networks the state of the art and comparative study"
    - "discovering social circles in ego networks"

Connected through hyperedge HE-2 (induced by source paper "high quality disjoint and overlapping community structure in large scale complex networks"):
  with members:
    - "dynamic structural similarity on graphs"
    - "personalized pagerank estimation and search a bidirectional approach"
    - "improving pagerank for local community detection"
    - "uncovering the small community structure in large networks a local spectral approach"
    - "heat kernel based community detection"
    - "community detection via local dynamic interaction"
    - "slpa uncovering overlapping communities in social networks via a speaker listener interaction dynamic process"

Connected through hyperedge HE-3 (induced by source paper "ensemble based discovery of disjoint overlapping and fuzzy community structures in networks"):
  with members:
    - "ensemble based algorithms to detect disjoint and overlapping communities in networks"
    - "permanence and community structure in complex networks"
    - "metrics for community analysis a survey"
    - "think locally act locally detection of small medium sized and large communities in large networks"
    - "personalized pagerank solution paths"
    - "yasca a collective intelligence approach for community detection in complex networks"
    - "overlapping community detection in networks the state of the art and comparative study"
    - "labelrankt incremental community detection in dynamic networks via label propagation"

Connected through hyperedge HE-4 (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-5 (induced by source paper "permanence and community structure in complex networks"):
  with members:
    - "genperm a unified method for detecting non overlapping and overlapping communities"
    - "a new metric for quality of network community structure"
    - "community detection and graph partitioning"
    - "enhancing community detection using a network weighting strategy"
    - "discovering link communities in complex networks by exploiting link dynamics"
    - "towards linear time overlapping community detection in social networks"
    - "comparative evaluation of community detection algorithms a topological approach"
    - "defining and evaluating network communities based on ground truth"

Connected through hyperedge HE-6 (induced by source paper "ensemble based algorithms to detect disjoint and overlapping communities in networks"):
  with members:
    - "think locally act locally detection of small medium sized and large communities in large networks"
    - "towards linear time overlapping community detection in social networks"
    - "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)