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: "top k color queries for document retrieval"
  Abstract: In this paper we describe a new efficient (in fact optimal) data structure for the {\em top-$K$ color problem}. Each element of an array $A$ is assigned a color $c$ with priority $p(c)$. For a query range $[a,b]$ and a value $K$, we have to report $K$ colors with the highest priorities among all colors that occur in $A[a..b]$, sorted in reverse order by their priorities. We show that such queries can be answered in $O(K)$ time using an $O(N\log \sigma)$ bits data structure, where $N$ is the number of elements in the array and $\sigma$ is the number of colors. Thus our data structure is asymptotically optimal with respect to the worst-case query time and space. As an immediate application of our results, we obtain optimal time solutions for several document retrieval problems. The method of the paper could be also of independent interest.

Connected through hyperedge HE-1 (induced by source paper "approximate range counting revisited"):
  with members:
    - "orthogonal range searching on the ram revisited"

Connected through hyperedge HE-2 (induced by source paper "optimal encodings for range majority queries"):
  with members:
    - "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"
    - "practical entropy compressed rank select dictionary"
    - "time space trade offs for predecessor search"

Connected through hyperedge HE-3 (induced by source paper "spaces trees and colors the algorithmic landscape of document retrieval on sequences"):
  with members:
    - "orthogonal range searching for text indexing"
    - "optimal top k document retrieval"
    - "on optimal top k string retrieval"
    - "faster compact top k document retrieval"
    - "new lower and upper bounds for representing sequences"
    - "towards an optimal space and query time index for top k document retrieval"
    - "space efficient data analysis queries on grids"
    - "new algorithms on wavelet trees and applications to information retrieval"

Connected through hyperedge HE-4 (induced by source paper "orthogonal range searching for text indexing"):
  with members:
    - "spaces trees and colors the algorithmic landscape of document retrieval on sequences"
    - "binary jumbled string matching for highly run length compressible texts"
    - "linear space substring range counting over polylogarithmic alphabets"
    - "compact binary relation representations with rich functionality"
    - "on optimal top k string retrieval"
    - "sorted range reporting"
    - "orthogonal range searching on the ram revisited"
    - "improved grammar based compressed indexes"

Connected through hyperedge HE-5 (induced by source paper "optimal top k document retrieval"):
  with members:
    - "fast prefix search in little space with applications"
    - "alphabet dependent string searching with wexponential search trees"
    - "spaces trees and colors the algorithmic landscape of document retrieval on sequences"
    - "faster compact top k document retrieval"
    - "orthogonal range searching on the ram revisited"
    - "towards an optimal space and query time index for top k document retrieval"
    - "space efficient data analysis queries on grids"
    - "new algorithms on wavelet trees and applications to information retrieval"

Connected through hyperedge HE-6 (induced by source paper "improved space time tradeoffs for approximate full text indexing with one edit error"):
  with members:
    - "fast prefix search in little space with applications"
    - "time space trade offs for longest common extensions"
    - "optimal succinctness for range minimum queries"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"

Connected through hyperedge HE-7 (induced by source paper "towards an optimal space and query time index for top k document retrieval"):
  with members:
    - "optimal trade off for succinct string indexes"
    - "range quantile queries another virtue of wavelet trees"
    - "optimal succinctness for range minimum queries"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"

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)