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 "range majorities and minorities in arrays"):
  Abstract: Karpinski and Nekrich (2008) introduced the problem of parameterized range majority, which asks us to preprocess a string of length $n$ such that, given the endpoints of a range, one can quickly find all the distinct elements whose relative frequencies in that range are more than a threshold $\tau$. Subsequent authors have reduced their time and space bounds such that, when $\tau$ is fixed at preprocessing time, we need either $O(n \log (1 / \tau))$ space and optimal $O(1 / \tau)$ query time or linear space and $O((1 / \tau) \log \log \sigma)$ query time, where $\sigma$ is the alphabet size. In this paper we give the first linear-space solution with optimal $O(1 / \tau)$ query time, even with variable $\tau$ (i.e., specified with the query). For the case when $\sigma$ is polynomial on the computer word size, our space is optimally compressed according to the symbol frequencies in the string. Otherwise, either the compressed space is increased by an arbitrarily small constant factor or the time rises to any function in $(1/\tau)\cdot\omega(1)$. We obtain the same results on the complementary problem of parameterized range minority introduced by Chan et al. (2015), who had achieved linear space and $O(1 / \tau)$ query time with variable $\tau$.

Includes members:
  Member "optimal encodings for range majority queries":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "compressed dynamic range majority and minority data structures")
  Member "optimal lower and upper bounds for representing sequences":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "energy consumption in compact integer vectors a study case")
  Member "dynamic range majority data structures":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "compressed dynamic range majority and minority data structures")
  Member "more haste less waste lowering the redundancy in fully indexable dictionaries":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "four dimensional dominance range reporting in linear space")
  Member "optimal succinctness for range minimum queries":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "space efficient construction of lyndon arrays in linear time")
  Member "searching for frequent colors in rectangles":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "compressed dynamic range majority and minority data structures")
  Member "range mode and range median queries on lists and trees":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "path query data structures in practice")

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)