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: "approximating lz77 via small space multiple pattern matching"
  Abstract: We generalize Karp-Rabin string matching to handle multiple patterns in $\mathcal{O}(n \log n + m)$ time and $\mathcal{O}(s)$ space, where $n$ is the length of the text and $m$ is the total length of the $s$ patterns, returning correct answers with high probability. As a prime application of our algorithm, we show how to approximate the LZ77 parse of a string of length $n$. If the optimal parse consists of $z$ phrases, using only $\mathcal{O}(z)$ working space we can return a parse consisting of at most $(1+\varepsilon)z$ phrases in $\mathcal{O}(\varepsilon^{-1}n\log n)$ time, for any $\varepsilon\in (0,1]$. As previous quasilinear-time algorithms for LZ77 use $\Omega(n/\textrm{polylog }n)$ space, but $z$ can be exponentially small in $n$, these improvements in space are substantial.

Connected through hyperedge HE-1 (induced by source paper "time space tradeoffs for finding a long common substring"):
  with members:
    - "faster queries for longest substring palindrome after block edit"
    - "locally consistent parsing for text indexing in small space"
    - "longest common substring made fully dynamic"
    - "sparse suffix tree construction in optimal time and space"
    - "longest common substrings with k mismatches"
    - "sublinear space algorithms for the longest common substring problem"

Connected through hyperedge HE-2 (induced by source paper "lempel ziv like parsing in small space"):
  with members:
    - "at the roots of dictionary compression string attractors"
    - "relations between greedy and bit optimal lz77 encodings"
    - "lz end parsing in compressed space"
    - "from theory to practice plug and play with succinct data structures"
    - "lempel ziv parsing in external memory"
    - "linear time lempel ziv factorization simple fast small"
    - "relative lempel ziv factorization for efficient storage and retrieval of web collections"
    - "large alphabets and incompressibility"

Connected through hyperedge HE-3 (induced by source paper "refining the r index"):
  with members:
    - "conversion from rlbwt to lz77"
    - "fully functional suffix trees and optimal text searching in bwt runs bounded space"
    - "lower bounds for text indexing with mismatches and differences"
    - "efficient construction of a complete index for pan genomics read alignment"
    - "prefix free parsing for building big bwts"
    - "from lz77 to the run length encoded burrows wheeler transform and back"
    - "a framework of dynamic data structures for string processing"
    - "optimal construction of compressed indexes for highly repetitive texts"

Connected through hyperedge HE-4 (induced by source paper "decompressing lempel ziv compressed text"):
  with members:
    - "mergeable dictionaries with shifts"
    - "time space trade offs for lempel ziv compressed indexing"
    - "lempel ziv decoding in external memory"
    - "linear time lempel ziv factorization simple fast small"
    - "pattern matching in lempel ziv compressed strings fast simple and deterministic"

Connected through hyperedge HE-5 (induced by source paper "lz end parsing in compressed space"):
  with members:
    - "faster lightweight lempel ziv parsing"
    - "range predecessor and lempel ziv parsing"
    - "lightweight lempel ziv parsing"
    - "lempel ziv parsing in external memory"

Connected through hyperedge HE-6 (induced by source paper "dynamic index lz factorization and lce queries in compressed space"):
  with members:
    - "online self indexed grammar compression"
    - "dynamic data structures for document collections and graphs"
    - "finger search random access and longest common extensions in grammar compressed strings"
    - "fingerprints in compressed strings"
    - "restructuring compressed texts without explicit decompression"

Connected through hyperedge HE-7 (induced by source paper "sampling the suffix array with minimizers"):
  with members:
    - "kmc 2 fast and resource frugal k mer counting"
    - "two simple full text indexes based on the suffix array"
    - "compressed text indexes from theory to practice"

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)