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 query time for encoding range majority"):
  Abstract: We revisit the range $\tau$-majority problem, which asks us to preprocess an array $A[1..n]$ for a fixed value of $\tau \in (0,1/2]$, such that for any query range $[i,j]$ we can return a position in $A$ of each distinct $\tau$-majority element. A $\tau$-majority element is one that has relative frequency at least $\tau$ in the range $[i,j]$: i.e., frequency at least $\tau (j-i+1)$. Belazzougui et al. [WADS 2013] presented a data structure that can answer such queries in $O(1/\tau)$ time, which is optimal, but the space can be as much as $\Theta(n \lg n)$ bits. Recently, Navarro and Thankachan [Algorithmica 2016] showed that this problem could be solved using an $O(n \lg (1/\tau))$ bit encoding, which is optimal in terms of space, but has suboptimal query time. In this paper, we close this gap and present a data structure that occupies $O(n \lg (1/\tau))$ bits of space, and has $O(1/\tau)$ query time. We also show that this space bound is optimal, even for the much weaker query in which we must decide whether the query range contains at least one $\tau$-majority element.

Includes members:
  Member "range majorities and minorities in arrays":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "compressed dynamic range majority and minority data structures")
  Member "optimal encodings for range majority queries":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "compressed dynamic range majority and minority data structures")
  Member "better space bounds for parameterized range majority and minority":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "compressed dynamic range majority and minority data structures")
  Member "searching for frequent colors in rectangles":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "compressed dynamic range majority and minority data structures")
  Member "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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)