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: "minimum clique partition in unit disk graphs"
  Abstract: The minimum clique partition (MCP) problem is that of partitioning the vertex set of a given graph into a minimum number of cliques. Given $n$ points in the plane, the corresponding unit disk graph (UDG) has these points as vertices, and edges connecting points at distance at most~1. MCP in unit disk graphs is known to be NP-hard and several constant factor approximations are known, including a recent PTAS. We present two improved approximation algorithms for minimum clique partition in unit disk graphs: #R##N#(I) A polynomial time approximation scheme (PTAS) running in time $n^{O(1/\eps^2)}$. This improves on a previous PTAS with $n^{O(1/\eps^4)}$ running time \cite{PS09}. #R##N#(II) A randomized quadratic-time algorithm with approximation ratio 2.16. This improves on a ratio 3 algorithm with $O(n^2)$ running time \cite{CFFP04}.

Connected through hyperedge HE-1 (induced by source paper "on arrangements of orthogonal circles"):
  with members:
    - "triangle free penny graphs degeneracy choosability and edge count"
    - "arrangements of pseudocircles triangles and drawings"

Connected through hyperedge HE-2 (induced by source paper "covering with clubs complexity and approximability"):
  with members:
    - "close communities in social networks boroughs and 2 clubs"
    - "a weakly robust ptas for minimum clique partition in unit disk graphs"

Connected through hyperedge HE-3 (induced by source paper "finding hitting and packing cycles in subexponential time on unit disk graphs"):
  with members:
    - "subexponential parameterized algorithms for planar and apex minor free graphs via low treewidth pattern covering"
    - "bidimensionality and kernels"
    - "approximation algorithms for polynomial expansion and low density graphs"
    - "mixing color coding related techniques"
    - "bidimensionality and geometric graphs"
    - "narrow sieves for parameterized paths and packings"
    - "bidimensionality and eptas"
    - "improved approximation algorithms for geometric set cover"

Connected through hyperedge HE-4 (induced by source paper "bidimensionality and geometric graphs"):
  with members:
    - "bidimensionality and kernels"
    - "bidimensionality and eptas"

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)