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: "fast distributed algorithms for testing graph properties"
  Abstract: We initiate a thorough study of \emph{distributed property testing} -- producing algorithms for the approximation problems of property testing in the CONGEST model. In particular, for the so-called \emph{dense} testing model we emulate sequential tests for nearly all graph properties having $1$-sided tests, while in the \emph{sparse} and \emph{general} models we obtain faster tests for triangle-freeness and bipartiteness respectively. #R##N#In most cases, aided by parallelism, the distributed algorithms have a much shorter running time as compared to their counterparts from the sequential querying model of traditional property testing. The simplest property testing algorithms allow a relatively smooth transitioning to the distributed model. For the more complex tasks we develop new machinery that is of independent interest. This includes a method for distributed maintenance of multiple random walks.

Connected through hyperedge HE-1 (induced by source paper "distributed testing of graph isomorphism in the congest model"):
  with members:
    - "distributed detection of cliques in dynamic networks"
    - "property testing of planarity in the congest model"
    - "distributed triangle detection via expander decomposition"
    - "detecting cliques in congest networks"
    - "distributed subgraph detection"
    - "fooling views a new lower bound technique for distributed computations under congestion"
    - "distributed detection of cycles"
    - "faster and simpler distributed algorithms for testing and correcting graph properties in the congest model"

Connected through hyperedge HE-2 (induced by source paper "walking randomly massively and efficiently"):
  with members:
    - "exponentially faster massively parallel maximal matching"
    - "simulating random walks on graphs in the streaming model"
    - "matching and mis for uniformly sparse graphs in the low memory mpc model"
    - "massively parallel algorithms for finding well connected components in sparse graphs"
    - "testing graph clusterability algorithms and lower bounds"
    - "sparsifying distributed algorithms with ramifications in massively parallel computation and centralized local computation"
    - "weighted matchings via unweighted augmentations"
    - "round compression for parallel graph algorithms in strongly sublinear space"

Connected through hyperedge HE-3 (induced by source paper "distributed detection of cliques in dynamic networks"):
  with members:
    - "fast and simple deterministic algorithms for highly dynamic networks"
    - "simple dynamic algorithms for maximal independent set and other problems"
    - "fully dynamic maximal independent set with sublinear update time"
    - "local distributed algorithms in highly dynamic networks"
    - "distributed triangle detection via expander decomposition"
    - "improved algorithms for fully dynamic maximal independent set"
    - "detecting cliques in congest networks"
    - "distributed subgraph detection"

Connected through hyperedge HE-4 (induced by source paper "parameterized distributed complexity theory a logical approach"):
  with members:
    - "almost global problems in the local model"
    - "parameterized distributed algorithms"
    - "progressive algorithms for domination and independence"
    - "first order interpretations of bounded expansion classes"
    - "new classes of distributed time complexity"
    - "a time hierarchy theorem for the local model"
    - "deterministic subgraph detection in broadcast congest"
    - "towards a complexity theory for the congested clique"

Connected through hyperedge HE-5 (induced by source paper "property testing of planarity in the congest model"):
  with members:
    - "minor excluded network families admit fast distributed algorithms"
    - "fiding forbidden minors in sublinear time a o n 1 2 o 1 query one sided tester for minor closed properties on bounded degree graphs"
    - "distributed subgraph detection"
    - "testing bounded arboricity"
    - "a sublinear tester for outerplanarity and other forbidden minors with one sided error"
    - "distributed detection of cycles"
    - "faster and simpler distributed algorithms for testing and correcting graph properties in the congest model"
    - "distributed property testing for subgraph freeness revisited"

Connected through hyperedge HE-6 (induced by source paper "detecting cliques in congest networks"):
  with members:
    - "improved distributed expander decomposition and nearly optimal triangle enumeration"
    - "distributed triangle detection via expander decomposition"
    - "fooling views a new lower bound technique for distributed computations under congestion"
    - "distributed detection of cycles"
    - "quadratic and near quadratic lower bounds for the congest model"
    - "triangle finding and listing in congest networks"
    - "deterministic subgraph detection in broadcast congest"
    - "tight bounds for distributed graph computations"

Connected through hyperedge HE-7 (induced by source paper "fooling views a new lower bound technique for distributed computations under congestion"):
  with members:
    - "symmetry breaking in the congest model time and message efficient algorithms for ruling sets"
    - "a simple deterministic distributed mst algorithm with near optimal time and message complexities"
    - "quadratic and near quadratic lower bounds for the congest model"
    - "tight bounds for distributed graph computations"
    - "distributed testing of excluded subgraphs"
    - "a time and message optimal distributed algorithm for minimum spanning trees"
    - "distributed construction of purely additive spanners"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"

Connected through hyperedge HE-8 (induced by source paper "on the multiparty communication complexity of testing triangle freeness"):
  with members:
    - "further algebraic algorithms in the congested clique model and applications to graph theoretic problems"
    - "distributed testing of excluded subgraphs"
    - "a hybrid sampling scheme for triangle counting"
    - "dynamic graph stream algorithms in o n space"
    - "approximately counting triangles in sublinear time"
    - "algebraic methods in the congested clique"
    - "optimal principal component analysis in distributed and streaming models"
    - "communication lower bounds for statistical estimation problems via a distributed data processing inequality"

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.DC(Distributed, Parallel, and Cluster Computing)