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: "simple and fast rounding algorithms for directed and node weighted multiway cut"
  Abstract: In Directed Multiway Cut(Dir-MC) the input is an edge-weighted directed graph $G=(V,E)$ and a set of $k$ terminal nodes $\{s_1,s_2,\ldots,s_k\} \subseteq V$; the goal is to find a min-weight subset of edges whose removal ensures that there is no path from $s_i$ to $s_j$ for any $i \neq j$. In Node-weighted Multiway Cut(Node-MC) the input is a node-weighted undirected graph $G$ and a set of $k$ terminal nodes $\{s_1,s_2,\ldots,s_k\} \subseteq V$; the goal is to remove a min-weight subset of nodes to disconnect each pair of terminals. Dir-MC admits a $2$-approximation [Naor, Zosin '97] and Node-MC admits a $2(1-\frac{1}{k})$-approximation [Garg, Vazirani, Yannakakis '94], both via rounding of LP relaxations. Previous rounding algorithms for these problems, from nearly twenty years ago, are based on careful rounding of an "optimum" solution to an LP relaxation. This is particularly true for Dir-MC for which the rounding relies on a custom LP formulation instead of the natural distance based LP relaxation [Naor, Zosin '97]. #R##N#In this paper we describe extremely simple and near linear-time rounding algorithms for Dir-MC and Node-MC via a natural distance based LP relaxation. The dual of this relaxation is a special case of the maximum multicommodity flow problem. Our algorithms achieve the same bounds as before but have the significant advantage in that they can work with "any feasible" solution to the relaxation. Consequently, in addition to obtaining "book" proofs of LP rounding for these two basic problems, we also obtain significantly faster approximation algorithms by taking advantage of known algorithms for computing near-optimal solutions for maximum multicommodity flow problems. We also investigate lower bounds for Dir-MC when $k=2$ and in particular prove that the integrality gap of the LP relaxation is $2$ even in directed planar graphs.

Connected through hyperedge HE-1 (induced by source paper "hypergraph cuts with general splitting functions"):
  with members:
    - "nonlinearity networks a 2020 vision"
    - "three hypergraph eigenvector centralities"
    - "simplicial closure and higher order link prediction"
    - "network flow based refinement for multilevel hypergraph partitioning"
    - "hypergraph partitioning for sparse matrix matrix multiplication"
    - "higher order organization of complex networks"
    - "a simple and strongly local flow based method for cut improvement"
    - "local distribution and the symmetry gap approximability of multiway partitioning problems"

Connected through hyperedge HE-2 (induced by source paper "downgrading to minimize connectivity"):
  with members:
    - "improved algorithms for mst and metric tsp interdiction"
    - "hardness and approximation for network flow interdiction"
    - "an o 1 approximation for minimum spanning tree interdiction"
    - "improved region growing and combinatorial algorithms for k route cut problems"
    - "multiway cut pairwise realizable distributions and descending thresholds"
    - "approximation algorithms and hardness of the k route cut problem"

Connected through hyperedge HE-3 (induced by source paper "global and fixed terminal cuts in digraphs"):
  with members:
    - "approximating multicut and the demand graph"
    - "an improved integrality gap for the calinescu karloff rabani relaxation for multiway cut"
    - "improved hardness for cut interdiction and firefighter problems"
    - "directed multicut with linearly ordered terminals"
    - "multiway cut pairwise realizable distributions and descending thresholds"
    - "rounding algorithms for a geometric embedding of minimum multiway cut"

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)