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: "planar graphs random walks and bipartiteness testing"
  Abstract: We initiate the study of property testing in arbitrary planar graphs. We prove that bipartiteness can be tested in constant time, improving on the previous bound of $\tilde{O}(\sqrt{n})$ for graphs on $n$ vertices. The constant-time testability was only known for planar graphs with bounded degree. #R##N#Our algorithm is based on random walks. Since planar graphs have good separators, i.e., bad expansion, our analysis diverges from standard techniques that involve the fast convergence of random walks on expanders. We reduce the problem to the task of detecting an odd-parity cycle in a multigraph induced by constant-length cycles. We iteratively reduce the length of cycles while preserving the detection probability, until the multigraph collapses to a collection of easily discoverable self-loops. #R##N#Our approach extends to arbitrary minor-free graphs. We also believe that our techniques will find applications to testing other properties in arbitrary minor-free graphs.

Connected through hyperedge HE-1 (induced by source paper "trapping problem on star type graphs with applications"):
  with members:
    - "on the structure and computation of random walk times in finite graphs"
    - "a vertex similarity index for better personalized recommendation"
    - "faster algorithms for computing the stationary distribution simulating random walks and more"
    - "reliability and survivability analysis of data center network topologies"
    - "convolutional random walk networks for semantic image segmentation"
    - "the constant inapproximability of the parameterized dominating set problem"
    - "estimating a random walk first passage time from noisy or delayed observations"

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 "testable properties in general graphs and random order streaming"):
  with members:
    - "a characterization of graph properties testable for general planar graphs with one sided error it is all about forbidden subgraphs"
    - "estimating graph parameters from random order streams"
    - "testable bounded degree graph properties are random order streamable"
    - "on estimating maximum matching size in graph streams"
    - "dynamic graph stream algorithms in o n space"
    - "testing forest isomorphism in the adjacency list model"

Connected through hyperedge HE-4 (induced by source paper "a characterization of graph properties testable for general planar graphs with one sided error it is all about forbidden subgraphs"):
  with members:
    - "testable properties in general graphs and random order streaming"
    - "on approximating the number of k cliques in sublinear time"
    - "approximately counting triangles in sublinear time"
    - "every property is testable on a natural class of scale free multigraphs"
    - "finding cycles and trees in sublinear time"

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 "testing bounded arboricity"):
  with members:
    - "on sampling edges almost uniformly"
    - "a quasi polynomial time partition oracle for graphs with an excluded minor"
    - "an efficient partitioning oracle for bounded treewidth graphs"
    - "finding cycles and trees in sublinear time"
    - "linear time algorithms for finding a dominating set of fixed size in degenerated graphs"

Connected through hyperedge HE-7 (induced by source paper "dynamic graph stream algorithms in o n space"):
  with members:
    - "correlation clustering in data streams"
    - "estimating graph parameters from random order streams"
    - "kernelization via sampling with applications to dynamic graph streams"
    - "densest subgraph in dynamic graph streams"
    - "sublinear estimation of weighted matchings in dynamic data streams"
    - "maximum matching in turnstile streams"
    - "applications of uniform sampling densest subgraph and beyond"
    - "space and time efficient algorithm for maintaining dense subgraphs on one pass dynamic streams"

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.DS(Data Structures and Algorithms)