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 "alibi an alignment based index for genomic datasets"):
  Abstract: With current hardware and software, a standard computer can now hold in RAM an index for approximate pattern matching on about half a dozen human genomes. Sequencing technologies have improved so quickly, however, that scientists will soon demand indexes for thousands of genomes. Whereas most researchers who have addressed this problem have proposed completely new kinds of indexes, we recently described a simple technique that scales standard indexes to work on more genomes. Our main idea was to filter the dataset with LZ77, build a standard index for the filtered file, and then create a hybrid of that standard index and an LZ77-based index. In this paper we describe how to our technique to use alignments instead of LZ77, in order to simplify and speed up both preprocessing and random access.

Includes members:
  Member "hybrid indexes for repetitive datasets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fully functional suffix trees and optimal text searching in bwt runs bounded space")
  Member "lempel ziv parsing in external memory":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "rpair rescaling repair with rsync")
  Member "data structure lower bounds on random access to grammar compressed strings":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fully functional suffix trees and optimal text searching in bwt runs bounded space")
  Member "orthogonal range searching on the ram revisited":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "path query data structures in practice")
  Member "improved grammar based compressed indexes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "top tree compression of tries")
  Member "a faster grammar based self index":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "top tree compression of tries")

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)