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: "finger search random access and longest common extensions in grammar compressed strings"
  Abstract: Grammar-based compression, where one replaces a long string by a small context-free grammar that generates the string, is a simple and powerful paradigm that captures many popular compression schemes. In this paper, we present new representations of grammars that supports efficient finger search style access, random access, and longest common extensions queries. Let $S$ be a string of length $N$ compressed into a context-free grammar $\mathcal{S}$ of size $n$. We present the following. #R##N#- An $O(n)$ space representation that supports setting a finger at any position $f$ in $O(\log N)$ time, and subsequently supporting access to any position $i$ in time $O(\log |f - i|)$. #R##N#- An $O(N^\epsilon n^{1-\epsilon})$ space representation that supports random access to any position in constant time. #R##N#- Two representations that support longest common extensions queries in either $O(N^{\frac{1}{2}+\epsilon} n^{\frac{1}{2}-\epsilon})$ space and $O(1)$ time or $O(n)$ space and $O(\log N + \log^2 \ell)$ time where $\ell$ is the length of the longest common extension. #R##N#All of the above bounds significantly improve the currently best known results. To achieve the bounds we introduce several new data structural techniques of independent interest, including a new van Emde Boas style decomposition for grammars.

Connected through hyperedge HE-1 (induced by source paper "fully dynamic data structure for lce queries in compressed space"):
  with members:
    - "optimal dynamic strings"
    - "longest common extensions in sublinear space"
    - "fingerprints in compressed strings"

Connected through hyperedge HE-2 (induced by source paper "dynamic index lz factorization and lce queries in compressed space"):
  with members:
    - "online self indexed grammar compression"
    - "approximating lz77 via small space multiple pattern matching"
    - "dynamic data structures for document collections and graphs"
    - "fingerprints in compressed strings"
    - "restructuring compressed texts without explicit decompression"

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)