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 "faster and smaller two level index for network based trajectories"):
  Abstract: Two-level indexes have been widely used to handle trajectories of moving objects that are constrained to a network. The top-level of these indexes handles the spatial dimension, whereas the bottom level handles the temporal dimension. The latter turns out to be an instance of the interval-intersection problem, but it has been tackled by non-specialized spatial indexes. In this work, we propose the use of a compact data structure on the bottom level of these indexes. Our experimental evaluation shows that our approach is both faster and smaller than existing solutions.

Includes members:
  Member "cinct compression and retrieval for massive vehicular trajectories via relative movement labeling":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a compact representation for trips over networks built on self indexes")
  Member "efficient compression and indexing of trajectories":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "about birds project bioinformatics and information retrieval data structures analysis and design")
  Member "gract a grammar based compressed representation of trajectories":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gract a grammar based compressed index for trajectory data")
  Member "compact trip representation over networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "about birds project bioinformatics and information retrieval data structures analysis and design")
  Member "composite repetition aware data structures":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on extensions of maximal repeats in compressed strings")
  Member "from theory to practice plug and play with succinct data structures":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "bitvectors with runs and the successor predecessor problem")
  Member "practical entropy compressed rank select dictionary":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "bitvectors with runs and the successor predecessor problem")

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)