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: "lines missing every random point"
  Abstract: We prove that there is, in every direction in Euclidean space, a line that misses every computably random point. We also prove that there exist, in every direction in Euclidean space, arbitrarily long line segments missing every double exponential time random point.

Connected through hyperedge HE-1 (induced by source paper "who asked us how the theory of computing answers questions about analysis"):
  with members:
    - "projection theorems using effective dimension"
    - "fractal intersections and products via algorithmic dimension"
    - "algorithmic information plane kakeya sets and conditional dimension"
    - "the dimensions of individual strings and sequences"

Connected through hyperedge HE-2 (induced by source paper "bounding the dimension of points on a line"):
  with members:
    - "algorithmic information plane kakeya sets and conditional dimension"
    - "effective dimension in some general metric spaces"
    - "dimension in complexity classes"
    - "the dimensions of individual strings and sequences"

Connected through hyperedge HE-3 (induced by source paper "algorithmic information plane kakeya sets and conditional dimension"):
  with members:
    - "mutual dimension and random sequences"
    - "points on computable curves"
    - "dimension in complexity classes"
    - "the dimensions of individual strings and sequences"

Connected through hyperedge HE-4 (induced by source paper "algorithmic information and plane kakeya sets"):
  with members:
    - "mutual dimension and random sequences"
    - "points on computable curves"
    - "dimension in complexity classes"
    - "the dimensions of individual strings and sequences"

Connected through hyperedge HE-5 (induced by source paper "polynomial space randomness in analysis"):
  with members:
    - "resource bounded measure"

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)