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: "advanced multilevel node separator algorithms"
  Abstract: A node separator of a graph is a subset S of the nodes such that removing S and its incident edges divides the graph into two disconnected components of about equal size. In this work, we introduce novel algorithms to find small node separators in large graphs. With focus on solution quality, we introduce novel flow-based local search algorithms which are integrated in a multilevel framework. In addition, we transfer techniques successfully used in the graph partitioning field. This includes the usage of edge ratings tailored to our problem to guide the graph coarsening algorithm as well as highly localized local search and iterated multilevel cycles to improve solution quality even further. Experiments indicate that flow-based local search algorithms on its own in a multilevel framework are already highly competitive in terms of separator quality. Adding additional local search algorithms further improves solution quality. Our strongest configuration almost always outperforms competing systems while on average computing 10% and 62% smaller separators than Metis and Scotch, respectively.

Connected through hyperedge HE-1 (induced by source paper "multilevel acyclic hypergraph partitioning"):
  with members:
    - "memetic graph clustering"
    - "network flow based refinement for multilevel hypergraph partitioning"
    - "scalable edge partitioning"
    - "graph partitioning with acyclicity constraints"
    - "memetic multilevel hypergraph partitioning"
    - "high quality shared memory graph partitioning"
    - "partitioning trillion edge graphs in minutes"
    - "k way hypergraph partitioning via n level recursive bisection"

Connected through hyperedge HE-2 (induced by source paper "scalable graph algorithms"):
  with members:
    - "exactly solving the maximum weight independent set problem on large real world graphs"
    - "memetic graph clustering"
    - "practical minimum cut algorithms"
    - "scalable edge partitioning"
    - "shared memory exact minimum cuts"
    - "scalable kernelization for maximum independent sets"
    - "graph partitioning with acyclicity constraints"
    - "memetic multilevel hypergraph partitioning"

Connected through hyperedge HE-3 (induced by source paper "faster and better nested dissection orders for customizable contraction hierarchies"):
  with members:
    - "graph bisection with pareto optimization"
    - "customizable contraction hierarchies"
    - "recent advances in graph partitioning"
    - "distributed evolutionary graph partitioning"

Connected through hyperedge HE-4 (induced by source paper "distributed evolutionary k way node separators"):
  with members:
    - "graph bisection with pareto optimization"
    - "a multilevel bilinear programming algorithm for the vertex separator problem"
    - "customizable contraction hierarchies"
    - "recent advances in graph partitioning"
    - "distributed evolutionary graph partitioning"

Connected through hyperedge HE-5 (induced by source paper "graph bisection with pareto optimization"):
  with members:
    - "fast exact shortest path and distance queries on road networks with parametrized costs"
    - "route planning in transportation networks"
    - "customizable contraction hierarchies"

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)