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: "lempel ziv decoding in external memory"
  Abstract: Simple and fast decoding is one of the main advantages of LZ77-type text encoding used in many popular file compressors such as gzip and 7zip. With the recent introduction of external memory algorithms for Lempel-Ziv factorization there is a need for external memory LZ77 decoding but the standard algorithm makes random accesses to the text and cannot be trivially modified for external memory computation. We describe the first external memory algorithms for LZ77 decoding, prove that their I/O complexity is optimal, and demonstrate that they are very fast in practice, only about three times slower than in-memory decoding (when reading input and writing output is included in the time).

Connected through hyperedge HE-1 (induced by source paper "bidirectional text compression in external memory"):
  with members:
    - "lzrr lz77 parsing with right reference"
    - "o n log n time text compression by lz style longest first substitution"
    - "at the roots of dictionary compression string attractors"
    - "compression with the tudocomp framework"
    - "lz end parsing in compressed space"
    - "lightweight lempel ziv parsing"
    - "lempel ziv parsing in external memory"
    - "simpler and faster lempel ziv factorization"

Connected through hyperedge HE-2 (induced by source paper "decompressing lempel ziv compressed text"):
  with members:
    - "mergeable dictionaries with shifts"
    - "time space trade offs for lempel ziv compressed indexing"
    - "approximating lz77 via small space multiple pattern matching"
    - "linear time lempel ziv factorization simple fast small"
    - "pattern matching in lempel ziv compressed strings fast simple and deterministic"

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)