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 "customizable contraction hierarchies"):
  Abstract: We consider the problem of quickly computing shortest paths in weighted graphs given auxiliary data derived in an expensive preprocessing phase. By adding a fast weight-customization phase, we extend Contraction Hierarchies by Geisberger et al to support the three-phase workflow introduced by Delling et al. Our Customizable Contraction Hierarchies use nested dissection orders as suggested by Bauer et al. We provide an in-depth experimental analysis on large road and game maps that clearly shows that Customizable Contraction Hierarchies are a very practicable solution in scenarios where edge weights often change.

Includes members:
  Member "graph bisection with pareto optimization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "load balanced bottleneck objectives in process mapping")
  Member "route planning in transportation networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "survey of deep reinforcement learning for motion planning of autonomous vehicles")
  Member "computing all pairs shortest paths by leveraging low treewidth":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "semi dynamic shortest path tree algorithms for directed graphs with arbitrary weights")
  Member "fast detour computation for ride sharing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the optimal route and stops for a group of users in a road network")
  Member "fast hierarchical clustering and other applications of dynamic closest pairs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "dynamic geometric data structures via shallow cuttings")

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)