human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "practical repetition aware grammar compression"):
  Abstract: The goal of grammar compression is to construct a small sized context free grammar which uniquely generates the input text data. Among grammar compression methods, RePair is known for its good practical compression performance. MR-RePair was recently proposed as an improvement to RePair for constructing small-sized context free grammar for repetitive text data. However, a compact encoding scheme has not been discussed for MR-RePair. We propose a practical encoding method for MR-RePair and show its effectiveness through comparative experiments. Moreover, we extend MR-RePair to run-length context free grammar and design a novel variant for it called RL-MR-RePair. We experimentally demonstrate that a compression scheme consisting of RL-MR-RePair and the proposed encoding method show good performance on real repetitive datasets.

Includes members:
  Member "mr repair grammar compression based on maximal repeats":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "grammar compression with probabilistic context free grammar")
  Member "repair in compressed space and time":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "re pair in place")
  Member "optimal time text indexing in bwt runs bounded space":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fast indexes for gapped pattern matching")
  Member "scalable partial least squares regression on grammar compressed data matrices":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "re pair in place")
  Member "space efficient re pair compression":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "grammar compression with probabilistic context free grammar")
  Member "online pattern matching for string edit distance with moves":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "siedm an efficient string index and search algorithm for edit distance with moves")
  Member "compact q gram profiling of compressed strings":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "scalable partial least squares regression on grammar compressed data matrices")
  Member "a succinct grammar compression":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "the smallest grammar problem revisited")

Question: Please tell me which class the source paper 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)