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: "indexing variation graphs"
  Abstract: Variation graphs, which represent genetic variation within a population, are replacing sequences as reference genomes. Path indexes are one of the most important tools for working with variation graphs. They generalize text indexes to graphs, allowing one to find the paths matching the query string. We propose using de Bruijn graphs as path indexes, compressing them by merging redundant subgraphs, and encoding them with the Burrows-Wheeler transform. The resulting fast, space-efficient, and versatile index is used in the variation graph toolkit vg.

Connected through hyperedge HE-1 (induced by source paper "graphs cannot be indexed in polynomial time for sub quadratic time string matching unless seth fails"):
  with members:
    - "regular languages meet prefix sorting"
    - "on prefix sorting finite automata"
    - "on the hardness and inapproximability of recognizing wheeler graphs"
    - "on the hardness of set disjointness and set intersection with bounded universe"
    - "lower bounds for text indexing with mismatches and differences"
    - "distributed pcp theorems for hardness of approximation in p"
    - "improving viterbi is hard better runtimes imply faster clique algorithms"
    - "the gremlin graph traversal machine and language invited talk"

Connected through hyperedge HE-2 (induced by source paper "lightweight merging of compressed indices based on bwt variants"):
  with members:
    - "space efficient merging of succinct de bruijn graphs"
    - "external memory bwt and lcp computation for sequence collections with applications"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "lightweight lcp construction for very large collections of strings"
    - "burrows wheeler transform for terabases"
    - "linear time construction of compressed text indices in compact space"
    - "variable order de bruijn graphs"

Connected through hyperedge HE-3 (induced by source paper "haplotype aware graph indexes"):
  with members:
    - "efficient construction of a complete index for pan genomics read alignment"
    - "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-4 (induced by source paper "using minimum path cover to boost dynamic programming on dags co linear chaining extended"):
  with members:
    - "read mapping on de bruijn graphs"
    - "linear time construction of compressed text indices in compact space"

Connected through hyperedge HE-5 (induced by source paper "relative compressed suffix trees"):
  with members:
    - "rlzap relative lempel ziv with adaptive pointers"
    - "composite repetition aware data structures"
    - "searching and indexing genomic databases via kernelization"
    - "from theory to practice plug and play with succinct data structures"
    - "fixed block compression boosting in fm indexes"
    - "a faster grammar based self index"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"
    - "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)