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: "compression with the tudocomp framework"
  Abstract: We present a framework facilitating the implementation and comparison of text compression algorithms. We evaluate its features by a case study on two novel compression algorithms based on the Lempel-Ziv compression schemes that perform well on highly repetitive texts.

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"
    - "lempel ziv decoding in external memory"
    - "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 "separate chaining meets compact hashing"):
  with members:
    - "packed compact tries a fast and efficient data structure for online string processing"
    - "practical evaluation of lempel ziv 78 and lempel ziv welch tries"

Connected through hyperedge HE-3 (induced by source paper "on the approximation ratio of greedy parsings"):
  with members:
    - "optimal time dictionary compressed indexes"
    - "at the roots of dictionary compression string attractors"
    - "optimal time text indexing in bwt runs bounded space"
    - "a separation between run length slps and lz77"
    - "fully dynamic data structure for lce queries in compressed space"
    - "composite repetition aware data structures"
    - "factorizations of the fibonacci infinite word"
    - "queries on lz bounded encodings"

Connected through hyperedge HE-4 (induced by source paper "lzrr lz77 parsing with right reference"):
  with members:
    - "on the approximation ratio of greedy parsings"
    - "at the roots of dictionary compression string attractors"
    - "a really simple approximation of smallest grammar"

Connected through hyperedge HE-5 (induced by source paper "practical evaluation of lempel ziv 78 and lempel ziv welch tries"):
  with members:
    - "dynamic space efficient hashing"
    - "faster 64 bit universal hashing using carry less multiplications"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "range predecessor and lempel ziv parsing"
    - "lempel ziv computation in compressed space lz cics"
    - "alphabet dependent string searching with wexponential search trees"
    - "lightweight lempel ziv parsing"
    - "lz compressed string dictionaries"

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)