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: "towards an optimal space and query time index for top k document retrieval"
  Abstract: Let $\D = $$ \{d_1,d_2,...d_D\}$ be a given set of $D$ string documents of total length $n$, our task is to index $\D$, such that the $k$ most relevant documents for an online query pattern $P$ of length $p$ can be retrieved efficiently. We propose an index of size $|CSA|+n\log D(2+o(1))$ bits and $O(t_{s}(p)+k\log\log n+poly\log\log n)$ query time for the basic relevance metric \emph{term-frequency}, where $|CSA|$ is the size (in bits) of a compressed full text index of $\D$, with $O(t_s(p))$ time for searching a pattern of length $p$ . We further reduce the space to $|CSA|+n\log D(1+o(1))$ bits, however the query time will be $O(t_s(p)+k(\log \sigma \log\log n)^{1+\epsilon}+poly\log\log n)$, where $\sigma$ is the alphabet size and $\epsilon >0$ is any constant.

Connected through hyperedge HE-1 (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"
    - "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-2 (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"
    - "space efficient data analysis queries on grids"
    - "new algorithms on wavelet trees and applications to information retrieval"
    - "top k color queries for document retrieval"

Connected through hyperedge HE-3 (induced by source paper "on optimal top k string retrieval"):
  with members:
    - "cross document pattern matching"

Connected through hyperedge HE-4 (induced by source paper "faster compact top k document retrieval"):
  with members:
    - "practical entropy compressed rank select dictionary"

Connected through hyperedge HE-5 (induced by source paper "practical top k document retrieval in reduced space"):
  with members:
    - "range quantile queries another virtue of wavelet 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)