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: "orthogonal range searching for text indexing"
  Abstract: Text indexing, the problem in which one desires to preprocess a (usually large) text for future (shorter) queries, has been researched ever since the suffix tree was invented in the early 70's. With textual data continuing to increase and with changes in the way it is accessed, new data structures and new algorithmic methods are continuously required. Therefore, text indexing is of utmost importance and is a very active research domain. #R##N#Orthogonal range searching, classically associated with the computational geometry community, is one of the tools that has increasingly become important for various text indexing applications. Initially, in the mid 90's there were a couple of results recognizing this connection. In the last few years we have seen an increase in use of this method and are reaching a deeper understanding of the range searching uses for text indexing. #R##N#In this monograph we survey some of these results.

Connected through hyperedge HE-1 (induced by source paper "time space trade offs for lempel ziv compressed indexing"):
  with members:
    - "fast prefix search in little space with applications"
    - "universal indexes for highly repetitive document collections"
    - "composite repetition aware data structures"
    - "searching and indexing genomic databases via kernelization"
    - "queries on lz bounded encodings"
    - "time space trade offs for longest common extensions"
    - "orthogonal range searching on the ram revisited"
    - "improved grammar based compressed indexes"

Connected through hyperedge HE-2 (induced by source paper "submatrix maximum queries in monge matrices are equivalent to predecessor search"):
  with members:
    - "improved submatrix maximum queries in monge matrices"
    - "succinct indices for range queries with applications to orthogonal range maxima"
    - "orthogonal range searching on the ram revisited"

Connected through hyperedge HE-3 (induced by source paper "spaces trees and colors the algorithmic landscape of document retrieval on sequences"):
  with members:
    - "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"
    - "optimal trade off for succinct string indexes"

Connected through hyperedge HE-4 (induced by source paper "internal pattern matching queries in a text and applications"):
  with members:
    - "wavelet trees meet suffix trees"
    - "sorted range reporting revisited"
    - "searching of gapped repeats and subrepetitions in a word"
    - "sorted range reporting"
    - "pattern matching in lempel ziv compressed strings fast simple and deterministic"
    - "on the maximal sum of exponents of runs in a string"

Connected through hyperedge HE-5 (induced by source paper "suffix trays and suffix trists structures for faster text indexing"):
  with members:
    - "on line indexing for general alphabets via predecessor queries on subsets of an ordered list"

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)