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: "tying up the loose ends in fully lzw compressed pattern matching"
  Abstract: We consider a natural generalization of the classical pattern matching problem: given compressed representations of a pattern p[1..M] and a text t[1..N] of sizes m and n, respectively, does p occur in t? We develop an optimal linear time solution for the case when both p and t are compressed using the LZW method. This improves the previously known O((n+m)log(n+m)) time solution of Gasieniec and Rytter, and essentially closes the line of research devoted to studying LZW-compressed exact pattern matching.

Connected through hyperedge HE-1 (induced by source paper "the complexity of compressed membership problems for finite automata"):
  with members:
    - "recompression a simple and powerful technique for word equations"
    - "pattern matching in lempel ziv compressed strings fast simple and deterministic"
    - "faster fully compressed pattern matching by recompression"
    - "random access to grammar compressed strings"

Connected through hyperedge HE-2 (induced by source paper "efficient lz78 factorization of grammar compressed text"):
  with members:
    - "speeding up q gram mining on grammar based compressed texts"
    - "lyndon words and short superstrings"
    - "a bijective string sorting transform"
    - "fast q gram mining on slp compressed strings"
    - "pattern matching in lempel ziv compressed strings fast simple and deterministic"
    - "faster fully compressed pattern matching by recompression"
    - "random access to grammar compressed strings"
    - "on bijective variants of the burrows wheeler transform"

Connected through hyperedge HE-3 (induced by source paper "faster fully compressed pattern matching by recompression"):
  with members:
    - "the complexity of compressed membership problems for finite automata"
    - "approximation of grammar based compression via recompression"
    - "approximation of smallest linear tree grammar"
    - "context unification is in pspace"
    - "one variable word equations in linear time"
    - "recompression a simple and powerful technique for word equations"
    - "pattern matching in lempel ziv compressed strings fast simple and deterministic"
    - "identifying hierarchical structure in sequences a linear time algorithm"

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)