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: "searching for frequent colors in rectangles"
  Abstract: We study a new variant of colored orthogonal range searching problem: given a query rectangle $Q$ all colors $c$, such that at least a fraction $\tau$ of all points in $Q$ are of color $c$, must be reported. We describe several data structures for that problem that use pseudo-linear space and answer queries in poly-logarithmic time.

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"
    - "optimal encodings for range majority queries"
    - "better space bounds for parameterized range majority and minority"
    - "optimal lower and upper bounds for representing sequences"
    - "dynamic range majority data structures"

Connected through hyperedge HE-2 (induced by source paper "optimal query time for encoding range majority"):
  with members:
    - "range majorities and minorities in arrays"
    - "optimal encodings for range majority queries"
    - "better space bounds for parameterized range majority and minority"
    - "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 encodings for range majority queries"
    - "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"
    - "range mode and range median queries on lists and trees"

Connected through hyperedge HE-4 (induced by source paper "compressed dynamic range majority data structures"):
  with members:
    - "range majorities and minorities in arrays"
    - "compressed data structures for dynamic sequences"
    - "dynamic range majority data structures"

Connected through hyperedge HE-5 (induced by source paper "optimal encodings for range majority queries"):
  with members:
    - "better space bounds for parameterized range majority and minority"
    - "top k color queries for document retrieval"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"
    - "practical entropy compressed rank select dictionary"
    - "time space trade offs for predecessor search"

Connected through hyperedge HE-6 (induced by source paper "better space bounds for parameterized range majority and minority"):
  with members:
    - "new lower and upper bounds for representing sequences"
    - "dynamic range majority data structures"
    - "efficient fully compressed sequence representations"
    - "optimal succinctness for range minimum queries"
    - "range mode and range median queries on lists and trees"
    - "dynamic ordered sets with exponential search trees"

Connected through hyperedge HE-7 (induced by source paper "space efficient data analysis queries on grids"):
  with members:
    - "orthogonal range searching on the ram revisited"
    - "new algorithms on wavelet trees and applications to information retrieval"
    - "succinct representations of dynamic strings"
    - "range quantile queries another virtue of wavelet trees"
    - "fully functional static and dynamic succinct trees"
    - "optimal succinctness for range minimum queries"
    - "practical entropy compressed rank select dictionary"

Connected through hyperedge HE-8 (induced by source paper "dynamic range majority data structures"):
  with members:
    - "better space bounds for parameterized range majority and minority"
    - "optimal dynamic sequence representations"
    - "space efficient data analysis queries on grids"
    - "dynamic range selection in linear space"
    - "counting colours in compressed strings"
    - "dynamic ordered sets with exponential search 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)