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: "new algorithms on wavelet trees and applications to information retrieval"
  Abstract: Wavelet trees are widely used in the representation of sequences, permutations, text collections, binary relations, discrete points, and other succinct data structures. We show, however, that this still falls short of exploiting all of the virtues of this versatile data structure. In particular we show how to use wavelet trees to solve fundamental algorithmic problems such as {\em range quantile} queries, {\em range next value} queries, and {\em range intersection} queries. We explore several applications of these queries in Information Retrieval, in particular {\em document retrieval} in hierarchical and temporal documents, and in the representation of {\em inverted lists}.

Connected through hyperedge HE-1 (induced by source paper "edge minimization in de bruijn graphs"):
  with members:
    - "tunneling on wheeler graphs"
    - "on undetected redundancy in the burrows wheeler transform"

Connected through hyperedge HE-2 (induced by source paper "a compact representation for trips over networks built on self indexes"):
  with members:
    - "cinct compression and retrieval for massive vehicular trajectories via relative movement labeling"
    - "compact trip representation over networks"
    - "efficient and compact representations of some non canonical prefix free codes"
    - "on compressing permutations and adaptive sorting"
    - "compressed text indexes from theory to practice"
    - "practical entropy compressed rank select dictionary"

Connected through hyperedge HE-3 (induced by source paper "document listing on repetitive collections with guaranteed performance"):
  with members:
    - "fast prefix search in little space with applications"
    - "universal compressed text indexing"
    - "time space trade offs for lempel ziv compressed indexing"
    - "compressed indexing with signature grammars"
    - "optimal time text indexing in bwt runs bounded space"
    - "document retrieval on repetitive string collections"
    - "fully dynamic data structure for lce queries in compressed space"
    - "composite repetition aware data structures"

Connected through hyperedge HE-4 (induced by source paper "m rwtl learning signal matched rational wavelet transform in lifting framework"):
  with members:
    - "image reconstruction using matched wavelet estimated from data sensed compressively using partial canonical identity matrix"
    - "reconnet non iterative reconstruction of images from compressively sensed random measurements"

Connected through hyperedge HE-5 (induced by source paper "document retrieval on repetitive string collections"):
  with members:
    - "universal indexes for highly repetitive document collections"
    - "composite repetition aware data structures"
    - "document retrieval on repetitive collections"
    - "spaces trees and colors the algorithmic landscape of document retrieval on sequences"
    - "from theory to practice plug and play with succinct data structures"
    - "faster compact top k document retrieval"
    - "improved grammar based compressed indexes"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"

Connected through hyperedge HE-6 (induced by source paper "parameterized pattern matching succinctly"):
  with members:
    - "linear time construction of compressed text indices in compact space"
    - "parameterized matching in the streaming model"
    - "succinct dictionary matching with no slowdown"

Connected through hyperedge HE-7 (induced by source paper "a representation of a compressed de bruijn graph for pan genome analysis that enables search"):
  with members:
    - "variable order de bruijn graphs"
    - "from theory to practice plug and play with succinct data structures"
    - "lightweight data indexing and compression in external memory"

Connected through hyperedge HE-8 (induced by source paper "efficient compressed wavelet trees over large alphabets"):
  with members:
    - "optimal dynamic sequence representations"
    - "new lower and upper bounds for representing sequences"
    - "on compressing permutations and adaptive sorting"
    - "succinct representations of dynamic strings"
    - "efficient fully compressed sequence representations"
    - "range quantile queries another virtue of wavelet trees"
    - "fully functional static and dynamic succinct trees"
    - "fast in memory xpath search over compressed text and tree indexes"

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)