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: "space efficient re pair compression"
  Abstract: Re-Pair is an effective grammar-based compression scheme achieving strong compression rates in practice. Let $n$, $\sigma$, and $d$ be the text length, alphabet size, and dictionary size of the final grammar, respectively. In their original paper, the authors show how to compute the Re-Pair grammar in expected linear time and $5n + 4\sigma^2 + 4d + \sqrt{n}$ words of working space on top of the text. In this work, we propose two algorithms improving on the space of their original solution. Our model assumes a memory word of $\lceil\log_2 n\rceil$ bits and a re-writable input text composed by $n$ such words. Our first algorithm runs in expected $\mathcal O(n/\epsilon)$ time and uses $(1+\epsilon)n +\sqrt n$ words of space on top of the text for any parameter $0<\epsilon \leq 1$ chosen in advance. Our second algorithm runs in expected $\mathcal O(n\log n)$ time and improves the space to $n +\sqrt n$ words.

Connected through hyperedge HE-1 (induced by source paper "grammar compression with probabilistic context free grammar"):
  with members:
    - "mr repair grammar compression based on maximal repeats"
    - "a grammar compression algorithm based on induced suffix sorting"
    - "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 "re pair in place"):
  with members:
    - "a study for image compression using re pair algorithm"
    - "a faster external memory priority queue with decreasekeys"
    - "mr repair grammar compression based on maximal repeats"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "practical repetition aware grammar compression"):
  with members:
    - "mr repair grammar compression based on maximal repeats"
    - "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"
    - "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"

Connected through hyperedge HE-4 (induced by source paper "mr repair grammar compression based on maximal repeats"):
  with members:
    - "representing the suffix tree with the cdawg"
    - "linear size cdawg new repetition aware indexing and grammar compression"
    - "fast label extraction in the cdawg"
    - "scalable partial least squares regression on grammar compressed data matrices"
    - "composite repetition aware data structures"

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)