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: "on the value of multiple read write streams for data compression"
  Abstract: We study whether, when restricted to using polylogarithmic memory and polylogarithmic passes, we can achieve qualitatively better data compression with multiple read/write streams than we can with only one. We first show how we can achieve universal compression using only one pass over one stream. We then show that one stream is not sufficient for us to achieve good grammar-based compression. Finally, we show that two streams are necessary and sufficient for us to achieve entropy-only bounds.

Connected through hyperedge HE-1 (induced by source paper "unidirectional input output streaming complexity of reversal and sorting"):
  with members:
    - "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"
    - "reversal complexity revisited"
    - "tight lower bounds for query processing on streaming and external memory data"

Connected through hyperedge HE-2 (induced by source paper "bounds from a card trick"):
  with members:
    - "large alphabets and incompressibility"

Connected through hyperedge HE-3 (induced by source paper "grammar based compression in a streaming model"):
  with members:
    - "random access to grammar compressed strings"
    - "recognizing well parenthesized expressions in the streaming model"
    - "lightweight data indexing and compression in external memory"
    - "reversal complexity revisited"

Connected through hyperedge HE-4 (induced by source paper "lightweight data indexing and compression in external memory"):
  with members:
    - "polylog space compression pushdown compression and lempel ziv are incomparable"

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.DS(Data Structures and Algorithms)