human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "searching and indexing genomic databases via kernelization"):
  Abstract: The rapid advance of DNA sequencing technologies has yielded databases of thousands of genomes. To search and index these databases effectively, it is important that we take advantage of the similarity between those genomes. Several authors have recently suggested searching or indexing only one reference genome and the parts of the other genomes where they differ. In this paper we survey the twenty-year history of this idea and discuss its relation to kernelization in parameterized complexity.

Includes members:
  Member "fully online grammar compression in constant space":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "grammar compression with probabilistic context free grammar")
  Member "hybrid indexes for repetitive datasets":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fully functional suffix trees and optimal text searching in bwt runs bounded space")
  Member "improved esp index a practical self index for highly repetitive texts":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a compressed dynamic self index for highly repetitive text collections")
  Member "indexes of large genome collections on a pc":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "efficient construction of a complete index for pan genomics read alignment")
  Member "data structure lower bounds on random access to grammar compressed strings":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fully functional suffix trees and optimal text searching in bwt runs bounded space")
  Member "faster approximate pattern matching in compressed repetitive texts":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fine grained complexity of analyzing compressed data quantifying improvements over decompress and solve")
  Member "improved grammar based compressed indexes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "top tree compression of tries")
  Member "random access to grammar compressed strings":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "local decode and update for big data compression")

Question: Please tell me which class the source paper 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)