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: "lightweight data indexing and compression in external memory"
  Abstract: In this paper we describe algorithms for computing the BWT and for building (compressed) indexes in external memory. The innovative feature of our algorithms is that they are lightweight in the sense that, for an input of size $n$, they use only ${n}$ bits of disk working space while all previous approaches use $\Th{n \log n}$ bits of disk working space. Moreover, our algorithms access disk data only via sequential scans, thus they take full advantage of modern disk features that make sequential disk accesses much faster than random accesses. #R##N#We also present a scan-based algorithm for inverting the BWT that uses $\Th{n}$ bits of working space, and a lightweight {\em internal-memory} algorithm for computing the BWT which is the fastest in the literature when the available working space is $\os{n}$ bits. #R##N#Finally, we prove {\em lower} bounds on the complexity of computing and inverting the BWT via sequential scans in terms of the classic product: internal-memory space $\times$ number of passes over the disk data.

Connected through hyperedge HE-1 (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"
    - "an external memory algorithm for string graph construction"
    - "linear time construction of compressed text indices in compact space"
    - "variable order de bruijn graphs"

Connected through hyperedge HE-2 (induced by source paper "prefix free parsing for building big bwts"):
  with members:
    - "from lz77 to the run length encoded burrows wheeler transform and back"
    - "optimal time text indexing in bwt runs bounded space"
    - "burrows wheeler transform for terabases"
    - "from theory to practice plug and play with succinct data structures"

Connected through hyperedge HE-3 (induced by source paper "burrows wheeler transform and lcp array construction in constant space"):
  with members:
    - "linear time string indexing and analysis in small space"
    - "low space external memory construction of the succinct permuted longest common prefix array"
    - "faster average case low memory semi external construction of the burrows wheeler transform"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "in place longest common extensions"
    - "lightweight lcp construction for very large collections of strings"
    - "linear time construction of compressed text indices in compact space"
    - "lightweight lcp construction for next generation sequencing datasets"

Connected through hyperedge HE-4 (induced by source paper "low space external memory construction of the succinct permuted longest common prefix array"):
  with members:
    - "faster average case low memory semi external construction of the burrows wheeler transform"
    - "sampled longest common prefix array"
    - "optimal succinctness for range minimum queries"

Connected through hyperedge HE-5 (induced by source paper "a representation of a compressed de bruijn graph for pan genome analysis that enables search"):
  with members:
    - "variable order de bruijn graphs"
    - "from theory to practice plug and play with succinct data structures"
    - "new algorithms on wavelet trees and applications to information retrieval"

Connected through hyperedge HE-6 (induced by source paper "from h m to gap for lightweight bwt merging"):
  with members:
    - "lightweight lcp construction for very large collections of strings"

Connected through hyperedge HE-7 (induced by source paper "a new lightweight algorithm to compute the bwt and the lcp array of a set of strings"):
  with members:
    - "lightweight lcp construction for next generation sequencing datasets"

Connected through hyperedge HE-8 (induced by source paper "burrows wheeler transform for terabases"):
  with members:
    - "a massively parallel algorithm for constructing the bwt of large string sets"
    - "from theory to practice plug and play with succinct data structures"
    - "large scale compression of genomic sequence databases with the burrows wheeler transform"
    - "practical entropy compressed rank select dictionary"

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)