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: "tight approximation ratio of a general greedy splitting algorithm for the minimum k way cut problem"
  Abstract: For an edge-weighted connected undirected graph, the minimum $k$-way cut problem is to find a subset of edges of minimum total weight whose removal separates the graph into $k$ connected components. The problem is NP-hard when $k$ is part of the input and W[1]-hard when $k$ is taken as a parameter. #R##N#A simple algorithm for approximating a minimum $k$-way cut is to iteratively increase the number of components of the graph by $h-1$, where $2 \le h \le k$, until the graph has $k$ components. The approximation ratio of this algorithm is known for $h \le 3$ but is open for $h \ge 4$. #R##N#In this paper, we consider a general algorithm that iteratively increases the number of components of the graph by $h_i-1$, where $h_1 \le h_2 \le ... \le h_q$ and $\sum_{i=1}^q (h_i-1) = k-1$. We prove that the approximation ratio of this general algorithm is $2 - (\sum_{i=1}^q {h_i \choose 2})/{k \choose 2}$, which is tight. Our result implies that the approximation ratio of the simple algorithm is $2-h/k + O(h^2/k^2)$ in general and $2-h/k$ if $k-1$ is a multiple of $h-1$.

Connected through hyperedge HE-1 (induced by source paper "the number of minimum k cuts improving the karger stein bound"):
  with members:
    - "lp relaxation and tree packing for minimum k cuts"
    - "fast and deterministic approximations for k cut"
    - "faster exact and approximate algorithms for k cut"
    - "an fpt algorithm beating 2 approximation for k cut"
    - "if the current clique algorithms are optimal so is valiant s parser"
    - "powers of tensors and fast matrix multiplication"
    - "designing fpt algorithms for cut problems using randomized contractions"
    - "minimum k way cut of bounded size is fixed parameter tractable"

Connected through hyperedge HE-2 (induced by source paper "faster minimum k cut of a simple graph"):
  with members:
    - "the number of minimum k cuts improving the karger stein bound"
    - "lp relaxation and tree packing for minimum k cuts"
    - "faster exact and approximate algorithms for k cut"
    - "local flow partitioning for faster edge connectivity"
    - "if the current clique algorithms are optimal so is valiant s parser"
    - "powers of tensors and fast matrix multiplication"
    - "deterministic edge connectivity in near linear time"
    - "designing fpt algorithms for cut problems using randomized contractions"

Connected through hyperedge HE-3 (induced by source paper "fast and deterministic approximations for k cut"):
  with members:
    - "lp relaxation and tree packing for minimum k cuts"
    - "on approximating sparse covering integer programs"
    - "faster exact and approximate algorithms for k cut"
    - "fast approximations for metric tsp via linear programming"
    - "an fpt algorithm beating 2 approximation for k cut"
    - "approximating the held karp bound for metric tsp in nearly linear time"
    - "deterministic global minimum cut of a simple graph in near linear time"
    - "nearly linear time approximation schemes for mixed packing covering and facility location linear programs"

Connected through hyperedge HE-4 (induced by source paper "faster exact and approximate algorithms for k cut"):
  with members:
    - "an fpt algorithm beating 2 approximation for k cut"
    - "powers of tensors and fast matrix multiplication"
    - "designing fpt algorithms for cut problems using randomized contractions"
    - "minimum cuts in near linear time"

Connected through hyperedge HE-5 (induced by source paper "inapproximability of maximum biclique problems minimum k cut and densest at least k subgraph from the small set expansion hypothesis"):
  with members:
    - "a birthday repetition theorem and complexity of approximating dense csps"
    - "analysis of boolean functions"
    - "analytical approach to parallel repetition"
    - "hardness of vertex deletion and project scheduling"
    - "reductions between expansion problems"
    - "the dense k subgraph problem"
    - "finding large and small dense subgraphs"

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)