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: "longest common extensions in sublinear space"
  Abstract: The longest common extension problem (LCE problem) is to construct a data structure for an input string $T$ of length $n$ that supports LCE$(i,j)$ queries. Such a query returns the length of the longest common prefix of the suffixes starting at positions $i$ and $j$ in $T$. This classic problem has a well-known solution that uses $O(n)$ space and $O(1)$ query time. In this paper we show that for any trade-off parameter $1 \leq \tau \leq n$, the problem can be solved in $O(\frac{n}{\tau})$ space and $O(\tau)$ query time. This significantly improves the previously best known time-space trade-offs, and almost matches the best known time-space product lower bound.

Connected through hyperedge HE-1 (induced by source paper "string indexing with compressed patterns"):
  with members:
    - "time space trade offs for lempel ziv compressed indexing"
    - "searching and indexing genomic databases via kernelization"
    - "improved grammar based compressed indexes"

Connected through hyperedge HE-2 (induced by source paper "universal compressed text indexing"):
  with members:
    - "fast prefix search in little space with applications"
    - "time space trade offs for lempel ziv compressed indexing"
    - "at the roots of dictionary compression string attractors"
    - "compressed indexing with signature grammars"
    - "fast label extraction in the cdawg"
    - "optimal time text indexing in bwt runs bounded space"
    - "sparse suffix tree construction in optimal time and space"
    - "a self index on block trees"

Connected through hyperedge HE-3 (induced by source paper "locally consistent parsing for text indexing in small space"):
  with members:
    - "string synchronizing sets sublinear time bwt construction and optimal lce data structure"
    - "sparse suffix tree construction in optimal time and space"
    - "tight lower bounds for the longest common extension problem"
    - "internal pattern matching queries in a text and applications"

Connected through hyperedge HE-4 (induced by source paper "in place longest common extensions"):
  with members:
    - "small space encoding lce data structure with constant time queries"
    - "burrows wheeler transform and lcp array construction in constant space"
    - "optimal time and space construction of suffix arrays and lcp arrays for integer alphabets"
    - "fast longest common extensions in small space"
    - "optimal in place suffix sorting"
    - "tight lower bounds for the longest common extension problem"
    - "dynamic index lz factorization and lce queries in compressed space"
    - "searching of gapped repeats and subrepetitions in a word"

Connected through hyperedge HE-5 (induced by source paper "tight lower bounds for the longest common extension problem"):
  with members:
    - "small space encoding lce data structure with constant time queries"
    - "fast longest common extensions in small space"
    - "faster longest common extension queries in strings over general alphabets"
    - "sparse suffix tree construction in optimal time and space"
    - "in place longest common extensions"
    - "longest common extensions with recompression"
    - "deterministic sub linear space lce data structures with efficient construction"
    - "computing runs on a general alphabet"

Connected through hyperedge HE-6 (induced by source paper "faster longest common extension queries in strings over general alphabets"):
  with members:
    - "the runs theorem"
    - "computing runs on a general alphabet"
    - "finding the leftmost critical factorization on unordered alphabet"
    - "online detection of repetitions with backtracking"
    - "lempel ziv factorization may be harder than computing all runs"

Connected through hyperedge HE-7 (induced by source paper "fully dynamic data structure for lce queries in compressed space"):
  with members:
    - "optimal dynamic strings"
    - "finger search random access and longest common extensions in grammar compressed strings"
    - "fingerprints in compressed strings"

Connected through hyperedge HE-8 (induced by source paper "fast longest common extensions in small space"):
  with members:
    - "dynamic index lz factorization and lce queries in compressed space"
    - "searching of gapped repeats and subrepetitions in a word"

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)