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: "complexity of metric dimension on planar graphs"
  Abstract: The metric dimension of a graph $G$ is the size of a smallest subset $L \subseteq V(G)$ such that for any $x,y \in V(G)$ with $x\not= y$ there is a $z \in L$ such that the graph distance between $x$ and $z$ differs from the graph distance between $y$ and $z$. Even though this notion has been part of the literature for almost 40 years, prior to our work the computational complexity of determining the metric dimension of a graph was still very unclear. In this paper, we show tight complexity boundaries for the Metric Dimension problem. We achieve this by giving two complementary results. First, we show that the Metric Dimension problem on planar graphs of maximum degree $6$ is NP-complete. Then, we give a polynomial-time algorithm for determining the metric dimension of outerplanar graphs.

Connected through hyperedge HE-1 (induced by source paper "metric dimension parameterized by treewidth"):
  with members:
    - "identification location domination and metric dimension on interval and permutation graphs i bounds"
    - "metric dimension of bounded tree length graphs"
    - "metric dimension parameterized by max leaf number"
    - "metric dimension for gabriel unit disk graphs is np complete"
    - "on the parameterized and approximation hardness of metric dimension"

Connected through hyperedge HE-2 (induced by source paper "alternative parameterizations of metric dimension"):
  with members:
    - "identification location domination and metric dimension on interval and permutation graphs ii algorithms and complexity"
    - "a polynomial turing kernel for weighted independent set in bull free graphs"
    - "metric dimension of bounded tree length graphs"
    - "metric dimension parameterized by max leaf number"
    - "characterizing the easy to find subgraphs from the viewpoint of polynomial time algorithms kernels and turing kernels"
    - "metric dimension for gabriel unit disk graphs is np complete"
    - "kernelization lower bounds by cross composition"
    - "non existence of polynomial kernels for the test cover problem"

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.CC(Computational Complexity)