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: "on the complexity of clustered level planarity and t level planarity"
  Abstract: In this paper we study two problems related to the drawing of level graphs, that is, T -LEVEL PLA- NARITY and CLUSTERED-LEVEL PLANARITY. We show that both problems are NP-complete in the general case and that they become polynomial-time solvable when restricted to proper instances. 1 Introduction and Overview A level graph is proper if any of its edges spans just two consecutive levels. Several papers about constructing level drawings of level graphs assume that the input graph is proper. Otherwise, they suggest to make it proper by "simply adding dummy vertices" along the edges spanning more than two levels. In this paper we show that this apparently innocent augmentation has dramatic consequences if, instead of constructing just a level drawing, we are also interested in representing additional constraints, like clustering of vertices or consecutivity constraints on the ordering of vertices on levels. A level graph G = (V;E; ) is a graph with a function : V ! f1;2;:::;kg, with 1 k j Vj such that (u)6 (v) for each edge (u;v)2 E. The setVi =fvj (v) = ig is thei-th level ofG. A level graphG = (V;E; ) is proper if for every edge (u;v)2 E, it holds (u) = (v) 1. A level planar drawing of (V;E; ) maps each vertex v of each levelVi to a point on liney = i, denoted byLi, and each edge to ay-monotone curve between its endpoints so that no two edges intersect. A level graph is level planar if it admits a level planar drawing. A linear-time algorithm for testing level planarity was presented by J¨ unger and Leipert in (10).

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)