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: "faster fully compressed pattern matching by recompression"
  Abstract: In this paper, a fully compressed pattern matching problem is studied. The compression is represented by straight-line programs (SLPs), i.e. a context-free grammars generating exactly one string; the term fully means that both the pattern and the text are given in the compressed form. The problem is approached using a recently developed technique of local recompression: the SLPs are refactored, so that substrings of the pattern and text are encoded in both SLPs in the same way. To this end, the SLPs are locally decompressed and then recompressed in a uniform way. #R##N#This technique yields an O((n+m)log M) algorithm for compressed pattern matching, assuming that M fits in O(1) machine words, where n (m) is the size of the compressed representation of the text (pattern, respectively), while M is the size of the decompressed pattern. If only m+n fits in O(1) machine words, the running time increases to O((n+m)log M log(n+m)). The previous best algorithm due to Lifshits had O(n^2m) running time.

Connected through hyperedge HE-1 (induced by source paper "grammar compression with probabilistic context free grammar"):
  with members:
    - "mr repair grammar compression based on maximal repeats"
    - "a grammar compression algorithm based on induced suffix sorting"
    - "space efficient re pair compression"
    - "fully online grammar compression in constant space"
    - "tree structure compression with repair"

Connected through hyperedge HE-2 (induced by source paper "practical repetition aware grammar compression"):
  with members:
    - "mr repair grammar compression based on maximal repeats"
    - "repair in compressed space and time"
    - "optimal time text indexing in bwt runs bounded space"
    - "scalable partial least squares regression on grammar compressed data matrices"
    - "space efficient re pair compression"
    - "online pattern matching for string edit distance with moves"
    - "compact q gram profiling of compressed strings"
    - "a succinct grammar compression"

Connected through hyperedge HE-3 (induced by source paper "balancing straight line programs"):
  with members:
    - "compressed range minimum queries"
    - "top tree compression of tries"
    - "grammar based compression of unranked trees"
    - "a universal tree balancing theorem"
    - "tree compression with top trees revisited"
    - "compressed subsequence matching and packed tree coloring"
    - "a really simple approximation of smallest grammar"
    - "approximation of grammar based compression via recompression"

Connected through hyperedge HE-4 (induced by source paper "internal dictionary matching"):
  with members:
    - "computing all distinct squares in linear time for integer alphabets"
    - "unifying and strengthening hardness for dynamic problems via the online matrix vector multiplication conjecture"
    - "wavelet trees meet suffix trees"
    - "internal pattern matching queries in a text and applications"
    - "recompression a simple and powerful technique for word equations"
    - "a linear time algorithm for seeds computation"

Connected through hyperedge HE-5 (induced by source paper "grammar based compression of unranked trees"):
  with members:
    - "balancing straight line programs"
    - "slowing down top trees for better worst case bounds"
    - "schemas for unordered xml on a dime"
    - "compressed tree canonization"
    - "tree compression with top trees revisited"
    - "context unification is in pspace"

Connected through hyperedge HE-6 (induced by source paper "compressed indexing with signature grammars"):
  with members:
    - "fast prefix search in little space with applications"
    - "time space trade offs for lempel ziv compressed indexing"
    - "optimal time text indexing in bwt runs bounded space"
    - "longest common extensions with recompression"
    - "dynamic index lz factorization and lce queries in compressed space"
    - "optimal dynamic strings"
    - "orthogonal range searching on the ram revisited"

Connected through hyperedge HE-7 (induced by source paper "longest common extensions with recompression"):
  with members:
    - "in place longest common extensions"
    - "finger search in grammar compressed strings"
    - "fingerprints in compressed strings"
    - "approximation of grammar based compression via recompression"
    - "approximation of smallest linear tree grammar"
    - "one variable word equations in linear time"
    - "recompression a simple and powerful technique for word equations"

Connected through hyperedge HE-8 (induced by source paper "tree compression using string grammars"):
  with members:
    - "tree compression with top trees revisited"
    - "a really simple approximation of smallest grammar"
    - "constructing small tree grammars and small circuits for formulas"
    - "linear compressed pattern matching for polynomial rewriting extended abstract"
    - "approximation of grammar based compression via recompression"
    - "approximation of smallest linear tree grammar"
    - "isomorphism of regular trees and words"

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)