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: "social hash partitioner a scalable distributed hypergraph partitioner"
  Abstract: We design and implement a distributed algorithm for balanced $k$-way hypergraph partitioning that minimizes fanout, a fundamental hypergraph quantity also known as the communication volume and ($k-1$)-cut metric, by optimizing a novel objective called probabilistic fanout. This choice allows a simple local search heuristic to achieve comparable solution quality to the best existing hypergraph partitioners. #R##N#Our algorithm is arbitrarily scalable due to a careful design that controls computational complexity, space complexity, and communication. In practice, we commonly process hypergraphs with billions of vertices and hyperedges in a few hours. We explain how the algorithm's scalability, both in terms of hypergraph size and bucket count, is limited only by the number of machines available. We perform an extensive comparison to existing distributed hypergraph partitioners and find that our approach is able to optimize hypergraphs roughly $100$ times bigger on the same set of machines. #R##N#We call the resulting tool Social Hash Partitioner (SHP), and accompanying this paper, we open-source the most scalable version based on recursive bisection.

Connected through hyperedge HE-1 (induced by source paper "distributed edge partitioning for trillion edge graphs"):
  with members:
    - "partitioning trillion edge graphs in minutes"
    - "effective techniques for message reduction and load balancing in distributed graph computation"
    - "spinner scalable graph partitioning in the cloud"
    - "recent advances in graph partitioning"
    - "defining and evaluating network communities based on ground truth"
    - "community structure in large networks natural cluster sizes and the absence of large well defined clusters"

Connected through hyperedge HE-2 (induced by source paper "hype massive hypergraph partitioning with neighborhood expansion"):
  with members:
    - "mesh a flexible distributed hypergraph processing system"
    - "adwise adaptive window based streaming edge partitioning for high speed graph processing"
    - "k way hypergraph partitioning via n level recursive bisection"
    - "spinner scalable graph partitioning in the cloud"

Connected through hyperedge HE-3 (induced by source paper "scalable edge partitioning"):
  with members:
    - "communication free massively distributed graph generation"
    - "engineering multilevel graph partitioning algorithms"

Connected through hyperedge HE-4 (induced by source paper "memetic multilevel hypergraph partitioning"):
  with members:
    - "k way hypergraph partitioning via n level recursive bisection"
    - "recent advances in graph partitioning"
    - "distributed evolutionary graph partitioning"
    - "engineering multilevel graph partitioning algorithms"

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)