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: "mr repair grammar compression based on maximal repeats"
  Abstract: We analyze the grammar generation algorithm of the RePair compression algorithm and show the relation between a grammar generated by RePair and maximal repeats. We reveal that RePair replaces step by step the most frequent pairs within the corresponding most frequent maximal repeats. Then, we design a novel variant of RePair, called MR-RePair, which substitutes the most frequent maximal repeats at once instead of substituting the most frequent pairs consecutively. We implemented MR-RePair and compared the size of the grammar generated by MR-RePair to that by RePair on several text corpus. Our experiments show that MR-RePair generates more compact grammars than RePair does, especially for highly repetitive texts.

Connected through hyperedge HE-1 (induced by source paper "grammar compression with probabilistic context free grammar"):
  with members:
    - "a grammar compression algorithm based on induced suffix sorting"
    - "space efficient re pair compression"
    - "fully online grammar compression in constant space"
    - "faster fully compressed pattern matching by recompression"
    - "tree structure compression with repair"

Connected through hyperedge HE-2 (induced by source paper "on extensions of maximal repeats in compressed strings"):
  with members:
    - "resolution of the burrows wheeler transform conjecture"
    - "composite repetition aware data structures"

Connected through hyperedge HE-3 (induced by source paper "rpair rescaling repair with rsync"):
  with members:
    - "gract a grammar based compressed index for trajectory data"
    - "prefix free parsing for building big bwts"
    - "time space trade offs for lempel ziv compressed indexing"
    - "compressed indexing with signature grammars"
    - "universal indexes for highly repetitive document collections"
    - "dynamic index lz factorization and lce queries in compressed space"
    - "a really simple approximation of smallest grammar"
    - "approximation of grammar based compression via recompression"

Connected through hyperedge HE-4 (induced by source paper "re pair in place"):
  with members:
    - "a study for image compression using re pair algorithm"
    - "a faster external memory priority queue with decreasekeys"
    - "repair in compressed space and time"
    - "burrows wheeler transform and lcp array construction in constant space"
    - "practical and effective re pair compression"
    - "optimal time and space construction of suffix arrays and lcp arrays for integer alphabets"
    - "optimal in place suffix sorting"
    - "scalable partial least squares regression on grammar compressed data matrices"

Connected through hyperedge HE-5 (induced by source paper "practical repetition aware grammar compression"):
  with members:
    - "repair in compressed space and time"
    - "optimal time text indexing in bwt runs bounded space"
    - "scalable partial least squares regression on grammar compressed data matrices"
    - "space efficient re pair compression"
    - "online pattern matching for string edit distance with moves"
    - "compact q gram profiling of compressed strings"
    - "a succinct grammar compression"
    - "approximation of grammar based compression via recompression"

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)