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: "efficient sub 5 approximations for minimum dominating sets in unit disk graphs"
  Abstract: Abstract   A unit disk graph is the intersection graph of n congruent disks in the plane. Dominating sets in unit disk graphs are widely studied due to their applicability in wireless ad-hoc networks. Because the minimum dominating set problem for unit disk graphs is NP-hard, numerous approximation algorithms have been proposed in the literature, including some PTASs. However, since the proposal of a linear-time 5-approximation algorithm in 1995, the lack of efficient algorithms attaining better approximation factors has aroused attention. We introduce an    O  (  n  +  m  )    algorithm that takes the usual adjacency representation of the graph as input and outputs a 44/9-approximation. This approximation factor is also attained by a second algorithm, which takes the geometric representation of the graph as input and runs in    O  (  n  log    n  )    time regardless of the number of edges. Additionally, we propose a 43/9-approximation which can be obtained in    O  (    n    2    m  )    time given only the graph's adjacency representation. It is noteworthy that the dominating sets obtained by our algorithms are also independent sets.

Connected through hyperedge HE-1 (induced by source paper "maximum matchings and minimum dominating sets in apollonian networks and extended tower of hanoi graphs"):
  with members:
    - "energy scaling of targeted optimal control of complex networks"
    - "on estimating maximum matching size in graph streams"
    - "maximum matchings in scale free networks with identical degree distribution"
    - "domination number and minimum dominating sets in pseudofractal scale free web and sierpinski graph"
    - "control principles of complex networks"

Connected through hyperedge HE-2 (induced by source paper "domination number and minimum dominating sets in pseudofractal scale free web and sierpinski graph"):
  with members:
    - "on the enumeration of minimal dominating sets and related notions"

Connected through hyperedge HE-3 (induced by source paper "linear time approximation algorithms for geometric intersection graphs"):
  with members:
    - "an almost linear time algorithm for approximate max flow in undirected graphs and its multicommodity generalizations"
    - "minimum dominating set for a point set in ir 2"
    - "approximation schemes for maximum weight independent set of rectangles"
    - "electrical flows laplacian systems and faster approximation of maximum flow in undirected graphs"

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)