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: "a ptas for tsp with neighborhoods among fat regions in the plane"
  Abstract: The Euclidean TSP with neighborhoods (TSPN) problem seeks a shortest tour that visits a given collection of $n$ regions ({\em neighborhoods}). We present the first polynomial-time approximation scheme for TSPN for a set of regions given by arbitrary disjoint fat regions in the plane. This improves substantially upon the known approximation algorithms, and is the first PTAS for TSPN on regions of non-comparable sizes. Our result is based on a novel extension of the $m$-guillotine method. The result applies to regions that are "fat" in a very weak sense: each region $P_i$ has area $\Omega([diam(P_i)]^2)$, but is otherwise arbitrary.

Connected through hyperedge HE-1 (induced by source paper "a ptas for euclidean tsp with hyperplane neighborhoods"):
  with members:
    - "chasing convex bodies optimally"
    - "competitively chasing convex bodies"
    - "nested convex bodies are chaseable"
    - "the traveling salesman problem low dimensionality implies a polynomial time approximation scheme"
    - "the traveling salesman problem for lines balls and planes"
    - "the traveling salesman problem for lines and rays in the plane"
    - "approximation algorithms for tsp with neighborhoods in the plane"

Connected through hyperedge HE-2 (induced by source paper "improved bounds for the traveling salesman problem with neighborhoods on uniform disks"):
  with members:
    - "constant factor approximation for tsp with disks"
    - "the traveling salesman problem for lines balls and planes"
    - "approximation algorithms for tsp with neighborhoods in the plane"

Connected through hyperedge HE-3 (induced by source paper "constant factor approximation for tsp with disks"):
  with members:
    - "the traveling salesman problem low dimensionality implies a polynomial time approximation scheme"
    - "the traveling salesman problem for lines balls and planes"
    - "the guillotine approach for tsp with neighborhoods revisited"
    - "violator spaces structure and algorithms"
    - "improved approximation algorithms for geometric set cover"
    - "approximation algorithms for tsp with neighborhoods in the plane"

Connected through hyperedge HE-4 (induced by source paper "tsp with locational uncertainty the adversarial model"):
  with members:
    - "approximation algorithms for tsp with neighborhoods in the plane"

Connected through hyperedge HE-5 (induced by source paper "the traveling salesman problem low dimensionality implies a polynomial time approximation scheme"):
  with members:
    - "efficient classification for metric data"
    - "a nonlinear approach to dimension reduction"
    - "how to complete a doubling metric"

Connected through hyperedge HE-6 (induced by source paper "the traveling salesman problem for lines balls and planes"):
  with members:
    - "constant factor approximation for tsp with disks"
    - "the traveling salesman problem low dimensionality implies a polynomial time approximation scheme"
    - "the stretch factor of the delaunay triangulation is less than 1 998"
    - "the guillotine approach for tsp with neighborhoods revisited"
    - "the traveling salesman problem for lines and rays in the plane"
    - "approximation algorithms for tsp with neighborhoods in the plane"

Connected through hyperedge HE-7 (induced by source paper "approximation algorithms for movement repairmen"):
  with members:
    - "local search based approximation algorithms for mobile facility location problems"
    - "minimizing movement fixed parameter tractability"
    - "facility location with client latencies linear programming based techniques for minimum latency problems"
    - "algorithms for rapidly dispersing robot swarms in unknown environments"
    - "approximation algorithms for tsp with neighborhoods in the plane"

Connected through hyperedge HE-8 (induced by source paper "minimum covering with travel cost"):
  with members:
    - "polygon exploration with discrete vision"
    - "polygon exploration with time discrete vision"
    - "approximation algorithms for tsp with neighborhoods in the plane"

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)