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 "efficient compressed wavelet trees over large alphabets"):
  Abstract: The {\em wavelet tree} is a flexible data structure that permits representing sequences $S[1,n]$ of symbols over an alphabet of size $\sigma$, within compressed space and supporting a wide range of operations on $S$. When $\sigma$ is significant compared to $n$, current wavelet tree representations incur in noticeable space or time overheads. In this article we introduce the {\em wavelet matrix}, an alternative representation for large alphabets that retains all the properties of wavelet trees but is significantly faster. We also show how the wavelet matrix can be compressed up to the zero-order entropy of the sequence without sacrificing, and actually improving, its time performance. Our experimental results show that the wavelet matrix outperforms all the wavelet tree variants along the space/time tradeoff map.

Includes members:
  Member "optimal dynamic sequence representations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "o log log n worst case local decoding and update efficiency for data compression")
  Member "new lower and upper bounds for representing sequences":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "run compressed rank select for large alphabets")
  Member "on compressing permutations and adaptive sorting":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on adaptive algorithms for maximum matching")
  Member "new algorithms on wavelet trees and applications to information retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "edge minimization in de bruijn graphs")
  Member "succinct representations of dynamic strings":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "compressed dynamic range majority and minority data structures")
  Member "efficient fully compressed sequence representations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "lyndon array construction during burrows wheeler inversion")
  Member "range quantile queries another virtue of wavelet trees":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "path query data structures in practice")
  Member "fully functional static and dynamic succinct trees":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "fully functional bidirectional burrows wheeler indexes")

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)