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: "the dimensions of individual strings and sequences"
  Abstract: A constructive version of Hausdorff dimension is developed using constructive supergales, which are betting strategies that generalize the constructive supermartingales used in the theory of individual random sequences. This constructive dimension is used to assign every individual (infinite, binary) sequence S a dimension, which is a real number dim(S) in the interval [0,1]. Sequences that are random (in the sense of Martin-Lof) have dimension 1, while sequences that are decidable, \Sigma^0_1, or \Pi^0_1 have dimension 0. It is shown that for every \Delta^0_2-computable real number \alpha in [0,1] there is a \Delta^0_2 sequence S such that \dim(S) = \alpha. #R##N#A discrete version of constructive dimension is also developed using termgales, which are supergale-like functions that bet on the terminations of (finite, binary) strings as well as on their successive bits. This discrete dimension is used to assign each individual string w a dimension, which is a nonnegative real number dim(w). The dimension of a sequence is shown to be the limit infimum of the dimensions of its prefixes. #R##N#The Kolmogorov complexity of a string is proven to be the product of its length and its dimension. This gives a new characterization of algorithmic information and a new proof of Mayordomo's recent theorem stating that the dimension of a sequence is the limit infimum of the average Kolmogorov complexity of its first n bits. #R##N#Every sequence that is random relative to any computable sequence of coin-toss biases that converge to a real number \beta in (0,1) is shown to have dimension \H(\beta), the binary entropy of \beta.

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"
    - "lines missing every random point"

Connected through hyperedge HE-2 (induced by source paper "asymptotic divergences and strong dichotomy"):
  with members:
    - "automatic kolmogorov complexity and normality revisited"
    - "computing absolutely normal numbers in nearly linear time"
    - "a divergence formula for randomness and dimension"
    - "dimensions of copeland erdos sequences"
    - "dimension in complexity classes"

Connected through hyperedge HE-3 (induced by source paper "on the incomputability of computable dimension"):
  with members:
    - "dimension in complexity classes"

Connected through hyperedge HE-4 (induced by source paper "dimension spectra of lines"):
  with members:
    - "bounding the dimension of points on a line"
    - "algorithmic information plane kakeya sets and conditional dimension"

Connected through hyperedge HE-5 (induced by source paper "bounding the dimension of points on a line"):
  with members:
    - "algorithmic information plane kakeya sets and conditional dimension"
    - "lines missing every random point"
    - "effective dimension in some general metric spaces"
    - "dimension in complexity classes"

Connected through hyperedge HE-6 (induced by source paper "mutual dimension and random sequences"):
  with members:
    - "analysis of boolean functions"
    - "a divergence formula for randomness and dimension"
    - "dimension in complexity classes"

Connected through hyperedge HE-7 (induced by source paper "fractal intersections and products via algorithmic dimension"):
  with members:
    - "bounding the dimension of points on a line"
    - "algorithmic information plane kakeya sets and conditional dimension"

Connected through hyperedge HE-8 (induced by source paper "bounded turing reductions and data processing inequalities for sequences"):
  with members:
    - "mutual dimension and random 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)