human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "optimal encodings for range majority queries"
  Abstract: We study the problem of designing a data structure that reports the positions of the distinct $\tau$-majorities within any range of an array $A[1,n]$, without storing $A$. A $\tau$-majority in a range $A[i,j]$, for $0<\tau< 1$, is an element that occurs more than $\tau(j-i+1)$ times in $A[i,j]$. We show that $\Omega(n\log(1/\tau))$ bits are necessary for any data structure able just to count the number of distinct $\tau$-majorities in any range. Then, we design a structure using $O(n\log(1/\tau))$ bits that returns one position of each $\tau$-majority of $A[i,j]$ in $O((1/\tau)\log\log_w(1/\tau)\log n)$ time, on a RAM machine with word size $w$ (it can output any further position where each $\tau$-majority occurs in $O(1)$ additional time). Finally, we show how to remove a $\log n$ factor from the time by adding $O(n\log\log n)$ bits of space to the structure.

Connected through hyperedge HE-1 (induced by source paper "compressed dynamic range majority and minority data structures"):
  with members:
    - "optimal query time for encoding range majority"
    - "range majorities and minorities in arrays"
    - "compressed dynamic range majority data structures"
    - "compressed data structures for dynamic sequences"
    - "better space bounds for parameterized range majority and minority"
    - "optimal lower and upper bounds for representing sequences"
    - "dynamic range majority data structures"
    - "succinct representations of dynamic strings"

Connected through hyperedge HE-2 (induced by source paper "optimal query time for encoding range majority"):
  with members:
    - "range majorities and minorities in arrays"
    - "better space bounds for parameterized range majority and minority"
    - "searching for frequent colors in rectangles"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"

Connected through hyperedge HE-3 (induced by source paper "range majorities and minorities in arrays"):
  with members:
    - "optimal lower and upper bounds for representing sequences"
    - "dynamic range majority data structures"
    - "more haste less waste lowering the redundancy in fully indexable dictionaries"
    - "optimal succinctness for range minimum queries"
    - "searching for frequent colors in rectangles"
    - "range mode and range median queries on lists and trees"

Question: Please tell me which class the center node 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)