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: "max flow vitality in general and planar graphs"
  Abstract: The vitality of an arc/node of a graph with respect to the maximum flow between two fixed nodes is defined as the reduction of the maximum flow caused by the removal of that arc/node. In this paper we address the issue of determining the vitality of arcs and/or nodes for the network flow problem over various classes of graphs and digraphs. First of all we show how to compute the vitality of all arcs in a general undirected graph by solving $n-1$ max flow instances, i.e., in worst case time $O(n \cdot \mbox{MF}(n,m))$, where $\mbox{MF}(n,m)$ is the time needed to solve a max-flow instance. In $st$-planar graphs (directed or undirected) we can compute the vitality of all arcs and all nodes in $O(n)$ worst case time. Moreover, after determining the vitality of arcs and/or nodes, and given a planar embedding of the graph, we can determine the vitality of a "contiguous" (w.r.t. that embedding) set of arcs/nodes in time proportional to the size of the set. In the case of general undirected planar graphs, the vitality of all nodes/arcs is computed in $O(n \log n)$ worst case time, while for the directed planar case we solve the same problem in $O(np)$, where $p$ is the number of arcs in a path from $s^{*}$ to $t^{*}$ in the dual graph.

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)