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: "an external memory algorithm for string graph construction"
  Abstract: Some recent results have introduced external-memory algorithms to compute self-indexes of a set of strings, mainly via computing the Burrows-Wheeler Transform (BWT) of the input strings. The motivations for those results stem from Bioinformatics, where a large number of short strings (called reads) are routinely produced and analyzed. In that field, a fundamental problem is to assemble a genome from a large set of much shorter samples extracted from the unknown genome. The approaches that are currently used to tackle this problem are memory-intensive. This fact does not bode well with the ongoing increase in the availability of genomic data. A data structure that is used in genome assembly is the string graph, where vertices correspond to samples and arcs represent two overlapping samples. In this paper we address an open problem: to design an external-memory algorithm to compute the string graph.

Connected through hyperedge HE-1 (induced by source paper "lyndon words versus inverse lyndon words queries on suffixes and bordered words"):
  with members:
    - "some variations on lyndon words"
    - "inverse lyndon words and inverse lyndon factorizations of words"
    - "on generalized lyndon words"
    - "the runs theorem"
    - "fsg fast string graph construction for de novo assembly of reads data"
    - "on the size of lempel ziv and lyndon factorizations"
    - "alternative algorithms for lyndon factorization"
    - "sorting suffixes of a text via its lyndon factorization"

Connected through hyperedge HE-2 (induced by source paper "external memory bwt and lcp computation for sequence collections with applications"):
  with members:
    - "the colored longest common prefix array computed via sequential scans"
    - "computing the bwt and lcp array of a set of strings in external memory"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "lightweight lcp construction for very large collections of strings"
    - "linear time construction of compressed text indices in compact space"
    - "variable order de bruijn graphs"
    - "lightweight data indexing and compression in external memory"

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)