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: "turning cliques into paths to achieve planarity"
  Abstract: Motivated by hybrid graph representations, we introduce and study the following beyond-planarity problem, which we call $h$-Clique2Path Planarity: Given a graph $G$, whose vertices are partitioned into subsets of size at most $h$, each inducing a clique, remove edges from each clique so that the subgraph induced by each subset is a path, in such a way that the resulting subgraph of $G$ is planar. We study this problem when $G$ is a simple topological graph, and establish its complexity in relation to $k$-planarity. We prove that $h$-Clique2Path Planarity is NP-complete even when $h=4$ and $G$ is a simple $3$-plane graph, while it can be solved in linear time, for any $h$, when $G$ is $1$-plane.

Connected through hyperedge HE-1 (induced by source paper "simultaneous fpq ordering and hybrid planarity testing"):
  with members:
    - "graph planarity testing with hierarchical embedding constraints"
    - "computing k modal embeddings of planar digraphs"
    - "nodetrix planarity testing with small clusters"
    - "computing nodetrix representations of clustered graphs"
    - "intersection link representations of graphs"
    - "beyond level planarity"
    - "simultaneous pq ordering with applications to constrained embedding problems"

Connected through hyperedge HE-2 (induced by source paper "computing k modal embeddings of planar digraphs"):
  with members:
    - "windrose planarity embedding graphs with direction constrained edges"
    - "nodetrix planarity testing with small clusters"
    - "planar l drawings of directed graphs"
    - "ordered level planarity geodesic planarity and bi monotonicity"
    - "computing nodetrix representations of clustered graphs"
    - "beyond level planarity"

Connected through hyperedge HE-3 (induced by source paper "a survey on graph drawing beyond planarity"):
  with members:
    - "parameterized complexity of 1 planarity"
    - "minimum weight connectivity augmentation for planar straight line graphs"
    - "compact drawings of 1 planar graphs with right angle crossings and few bends"
    - "drawing subcubic 1 planar graphs with few bends few slopes and large angles"
    - "a heuristic approach towards drawings of graphs with high crossing resolution"
    - "on rac drawings of graphs with one bend per edge"
    - "recognizing optimal 1 planar graphs in linear time"
    - "orthogonal and smooth orthogonal layouts of 1 planar graphs with low edge complexity"

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)