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: "possibilities and impossibilities in kolmogorov complexity extraction"
  Abstract: Randomness extraction is the process of constructing a source of randomness of high quality from one or several sources of randomness of lower quality. The problem can be modeled using probability distributions and min-entropy to measure their quality and also by using individual strings and Kolmogorov complexity to measure their quality. Complexity theorists are more familiar with the first approach. In this paper we survey the second approach. We present the connection between extractors and Kolmogorov extractors and the basic positive and negative results concerning Kolmogorov complexity extraction.

Connected through hyperedge HE-1 (induced by source paper "short lists with short programs in short time"):
  with members:
    - "short lists with short programs in short time a short proof"
    - "space bounded kolmogorov extractors"
    - "nonuniform kolmogorov extractors"
    - "short lists for shortest descriptions in short time"
    - "complexity of complexity and strings with maximal plain and prefix kolmogorov complexity"
    - "symmetry of information and bounds on nonuniform randomness extraction via kolmogorov extractors"
    - "improving the space bounded version of muchnik s conditional complexity theorem via naive derandomization"
    - "variations on muchnik s conditional complexity theorem"

Connected through hyperedge HE-2 (induced by source paper "space bounded kolmogorov extractors"):
  with members:
    - "symmetry of information and bounds on nonuniform randomness extraction via kolmogorov extractors"
    - "on the optimal compression of sets in pspace"
    - "pseudo random graphs and bit probe schemes with one sided error"
    - "impossibility of independence amplification in kolmogorov complexity theory"
    - "improving the space bounded version of muchnik s conditional complexity theorem via naive derandomization"
    - "extracting the kolmogorov complexity of strings and sequences from sources with limited independence"
    - "two sources are better than one for increasing the kolmogorov complexity of infinite sequences"

Connected through hyperedge HE-3 (induced by source paper "symmetry of information a closer look"):
  with members:
    - "symmetry of information and bounds on nonuniform randomness extraction via kolmogorov extractors"
    - "counting dependent and independent strings"
    - "extracting the kolmogorov complexity of strings and sequences from sources with limited independence"

Connected through hyperedge HE-4 (induced by source paper "nonuniform kolmogorov extractors"):
  with members:
    - "symmetry of information and bounds on nonuniform randomness extraction via kolmogorov extractors"
    - "improving the space bounded version of muchnik s conditional complexity theorem via naive derandomization"

Connected through hyperedge HE-5 (induced by source paper "on the optimal compression of sets in pspace"):
  with members:
    - "symmetry of information and bounds on nonuniform randomness extraction via kolmogorov extractors"
    - "improving the space bounded version of muchnik s conditional complexity theorem via naive derandomization"

Connected through hyperedge HE-6 (induced by source paper "symmetry of information and bounds on nonuniform randomness extraction via kolmogorov extractors"):
  with members:
    - "improving the space bounded version of muchnik s conditional complexity theorem via naive derandomization"

Connected through hyperedge HE-7 (induced by source paper "counting dependent and independent strings"):
  with members:
    - "impossibility of independence amplification in kolmogorov complexity theory"
    - "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"

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)