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 c k r partitions of sparse graphs"
  Abstract: We present fast algorithms for constructing probabilistic embeddings and approximate distance oracles in sparse graphs. The main ingredient is a fast algorithm for sampling the probabilistic partitions of Calinescu, Karloff, and Rabani in sparse graphs.

Connected through hyperedge HE-1 (induced by source paper "parallel metric tree embedding based on an algebraic view on moore bellman ford"):
  with members:
    - "parallelism in randomized incremental algorithms"
    - "near optimal approximate shortest paths and transshipment in distributed and streaming models"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "efficient construction of probabilistic tree embeddings"
    - "hopsets with constant hopbound and applications to approximate shortest paths"
    - "an almost tight distributed algorithm for computing single source shortest paths"
    - "a deterministic almost tight distributed algorithm for approximating single source shortest paths"
    - "fast partial distance estimation and applications"

Connected through hyperedge HE-2 (induced by source paper "approximate greedy clustering and distance selection for graph metrics"):
  with members:
    - "net and prune a linear time algorithm for euclidean distance problems"
    - "all distances sketches revisited hip estimators for massive graphs analysis"
    - "fast construction of nets in low dimensional metrics and their applications"
    - "the ariadne s clew algorithm"

Connected through hyperedge HE-3 (induced by source paper "approximate distance oracle with constant query time"):
  with members:
    - "approximate distance oracles with improved query time"
    - "approximate distance oracles with improved preprocessing time"
    - "ramsey partitions and proximity data structures"

Connected through hyperedge HE-4 (induced by source paper "approximate distance oracles with improved query time"):
  with members:
    - "approximate distance oracles with improved preprocessing time"
    - "ramsey partitions and proximity data structures"
    - "all pairs shortest paths using bridging sets and rectangular matrix multiplication"

Connected through hyperedge HE-5 (induced by source paper "fast precise and dynamic distance queries"):
  with members:
    - "a constructive proof of the general lovasz local lemma"
    - "ramsey partitions and proximity data structures"
    - "fast construction of nets in low dimensional metrics and their applications"

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)