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: "constructive dimension and turing degrees"
  Abstract: This paper examines the constructive Hausdorff and packing dimensions of Turing degrees. The main result is that every infinite sequence S with constructive Hausdorff dimension dim_H(S) and constructive packing dimension dim_P(S) is Turing equivalent to a sequence R with dim_H(R)   0. Furthermore, if dim_P(S) > 0, then dim_P(R) >= 1 - epsilon. The reduction thus serves as a *randomness extractor* that increases the algorithmic randomness of S, as measured by constructive dimension. #R##N#A number of applications of this result shed new light on the constructive dimensions of Turing degrees. A lower bound of dim_H(S) / dim_P(S) is shown to hold for the Turing degree of any sequence S. A new proof is given of a previously-known zero-one law for the constructive packing dimension of Turing degrees. It is also shown that, for any regular sequence S (that is, dim_H(S) = dim_P(S)) such that dim_H(S) > 0, the Turing degree of S has constructive Hausdorff and packing dimension equal to 1. #R##N#Finally, it is shown that no single Turing reduction can be a universal constructive Hausdorff dimension extractor, and that bounded Turing reductions cannot extract constructive Hausdorff dimension. We also exhibit sequences on which weak truth-table and bounded Turing reductions differ in their ability to extract dimension.

Connected through hyperedge HE-1 (induced by source paper "possibilities and impossibilities in kolmogorov complexity extraction"):
  with members:
    - "counting dependent and independent strings"
    - "impossibility of independence amplification in kolmogorov complexity theory"
    - "extracting the kolmogorov complexity of strings and sequences from sources with limited independence"
    - "algorithmically independent sequences"
    - "two sources are better than one for increasing the kolmogorov complexity of infinite sequences"
    - "dimension extractors and optimal decompression"

Connected through hyperedge HE-2 (induced by source paper "impossibility of independence amplification in kolmogorov complexity theory"):
  with members:
    - "extracting the kolmogorov complexity of strings and sequences from sources with limited independence"
    - "on generating independent random strings"
    - "two sources are better than one for increasing the kolmogorov complexity of infinite sequences"

Connected through hyperedge HE-3 (induced by source paper "extracting the kolmogorov complexity of strings and sequences from sources with limited independence"):
  with members:
    - "algorithmically independent sequences"
    - "two sources are better than one for increasing the kolmogorov complexity of infinite sequences"

Connected through hyperedge HE-4 (induced by source paper "algorithmically independent sequences"):
  with members:
    - "on generating independent random strings"
    - "two sources are better than one for increasing the kolmogorov complexity of infinite sequences"
    - "shannon information and kolmogorov complexity"
    - "independence properties of algorithmically random sequences"
    - "the dimensions of individual strings and sequences"

Connected through hyperedge HE-5 (induced by source paper "two sources are better than one for increasing the kolmogorov complexity of infinite sequences"):
  with members:
    - "extracting the kolmogorov complexity of strings and sequences from sources with limited independence"
    - "algorithmically independent sequences"
    - "dimension extractors and optimal decompression"
    - "the dimensions of individual strings and sequences"

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)