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: "strip planarity testing of embedded planar graphs"
  Abstract: In this paper we introduce and study the strip planarity testing problem, which takes as an input a planar graph $G(V,E)$ and a function $\gamma:V \rightarrow \{1,2,\dots,k\}$ and asks whether a planar drawing of $G$ exists such that each edge is monotone in the $y$-direction and, for any $u,v\in V$ with $\gamma(u)<\gamma(v)$, it holds $y(u)<y(v)$. The problem has strong relationships with some of the most deeply studied variants of the planarity testing problem, such as clustered planarity, upward planarity, and level planarity. We show that the problem is polynomial-time solvable if $G$ has a fixed planar embedding.

Connected through hyperedge HE-1 (induced by source paper "upward book embeddings of st graphs"):
  with members:
    - "upward planar morphs"
    - "windrose planarity embedding graphs with direction constrained edges"
    - "crossing minimization for 1 page and 2 page drawings of graphs with bounded treewidth"
    - "upward partitioned book embeddings"
    - "planar l drawings of directed graphs"
    - "arc diagrams flip distances and hamiltonian triangulations"
    - "the book thickness of 1 planar graphs is constant"
    - "intersection link representations of graphs"

Connected through hyperedge HE-2 (induced by source paper "recognizing weak embeddings of graphs"):
  with members:
    - "clustered planarity flat clustered planarity"
    - "hanani tutte for approximating maps of graphs"
    - "clustered planarity with pipes"
    - "recognizing weakly simple polygons"
    - "embedding graphs into embedded graphs"
    - "detecting weakly simple polygons"

Connected through hyperedge HE-3 (induced by source paper "detecting weakly simple polygons"):
  with members:
    - "connecting polygonizations via stretches and twangs"
    - "randomization yields simple o n log star n algorithms for difficult omega n problems"

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.CG(Computational Geometry)