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 "optimal lower and upper bounds for representing sequences"):
  Abstract: Sequence representations supporting queries $access$, $select$ and $rank$ are at the core of many data structures. There is a considerable gap between the various upper bounds and the few lower bounds known for such representations, and how they relate to the space used. In this article we prove a strong lower bound for $rank$, which holds for rather permissive assumptions on the space used, and give matching upper bounds that require only a compressed representation of the sequence. Within this compressed space, operations $access$ and $select$ can be solved in constant or almost-constant time, which is optimal for large alphabets. Our new upper bounds dominate all of the previous work in the time/space map.

Includes members:
  Member "new lower and upper bounds for representing sequences":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "run compressed rank select for large alphabets")
  Member "optimal trade off for succinct string indexes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "grammar compressed sequences with rank select support")
  Member "efficient fully compressed sequence representations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "lyndon array construction during burrows wheeler inversion")
  Member "compressed representations of permutations and applications":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "compression in the space of permutations")
  Member "fast in memory xpath search over compressed text and tree indexes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "efficient compressed wavelet trees over large alphabets")
  Member "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "path query data structures in practice")
  Member "large alphabets and incompressibility":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "lempel ziv like parsing in small space")
  Member "practical entropy compressed rank select dictionary":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "bitvectors with runs and the successor predecessor problem")

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)