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: "reversal complexity revisited"
  Abstract: We study a generalized version of reversal bounded Turing machines where, apart from several tapes on which the number of head reversals is bounded by r(n), there are several further tapes on which head reversals remain unrestricted, but size is bounded by s(n). Recently, such machines were introduced as a formalization of a computation model that restricts random access to external memory and internal memory space. Here, each of the tapes with a restriction on the head reversals corresponds to an external memory device, and the tapes of restricted size model internal memory. We use ST(r(n),s(n),O(1)) to denote the class of all problems that can be solved by deterministic Turing machines that comply to the above resource bounds. Similarly, NST and RST, respectively, are used for the corresponding nondeterministic and randomized classes. #R##N#While previous papers focused on lower bounds for particular problems, including sorting, the set equality problem, and several query evaluation problems, the present paper addresses the relations between the (R,N)ST-classes and classical complexity classes and investigates the structural complexity of the (R,N)ST-classes. Our main results are (1) a trade-off between internal memory space and external memory head reversals, (2) correspondences between the (R,N)ST-classes and ``classical'' time-bounded, space-bounded, reversal-bounded, and circuit complexity classes, and (3) hierarchies of (R)ST-classes in terms of increasing numbers of head reversals on external memory tapes.

Connected through hyperedge HE-1 (induced by source paper "unidirectional input output streaming complexity of reversal and sorting"):
  with members:
    - "on the value of multiple read write streams for data compression"
    - "streaming complexity of checking priority queues"
    - "data oblivious external memory algorithms for the compaction selection and sorting of outsourced data"
    - "information cost tradeoffs for augmented index and streaming language recognition"
    - "validating xml documents in the streaming model with external memory"
    - "the space complexity of recognizing well parenthesized expressions in the streaming model the index function revisited"
    - "recognizing well parenthesized expressions in the streaming model"
    - "tight lower bounds for query processing on streaming and external memory data"

Connected through hyperedge HE-2 (induced by source paper "on the value of multiple read write streams for data compression"):
  with members:
    - "grammar based compression in a streaming model"
    - "lightweight data indexing and compression in external memory"
    - "large alphabets and incompressibility"
    - "tight lower bounds for query processing on streaming and external memory data"

Connected through hyperedge HE-3 (induced by source paper "new algorithms and lower bounds for sequential access data compression"):
  with members:
    - "on optimally partitioning a text to improve its compression"
    - "low memory adaptive prefix coding"
    - "dynamic asymmetric communication"
    - "large alphabets and incompressibility"
    - "tight lower bounds for query processing on streaming and external memory data"
    - "dynamic shannon coding"

Connected through hyperedge HE-4 (induced by source paper "grammar based compression in a streaming model"):
  with members:
    - "on the value of multiple read write streams for data compression"
    - "random access to grammar compressed strings"
    - "recognizing well parenthesized expressions in the streaming model"
    - "lightweight data indexing and compression in external memory"

Connected through hyperedge HE-5 (induced by source paper "tight lower bounds for query processing on streaming and external memory data"):
  with members:
    - "randomized computations on large data sets tight lower bounds"
    - "monadic datalog and the expressive power of languages for web information extraction"

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)