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: "fast detour computation for ride sharing"
  Abstract: Todays ride sharing services still mimic a better billboard. They list the offers and allow to search for the source and target city, sometimes enriched with radial search. So finding a connection between big cities is quite easy. These places are on a list of designated origin and distination points. But when you want to go from a small town to another small town, even when they are next to a freeway, you run into problems. You can't find offers that would or could pass by the town easily with little or no detour. We solve this interesting problem by presenting a fast algorithm that computes the offers with the smallest detours w.r.t. a request. Our experiments show that the problem is efficiently solvable in times suitable for a web service implementation. For realistic database size we achieve lookup times of about 5ms and a matching rate of 90% instead of just 70% for the simple matching algorithms used today.

Connected through hyperedge HE-1 (induced by source paper "the optimal route and stops for a group of users in a road network"):
  with members:
    - "shortest path and distance queries on road networks towards bridging theory and practice"

Connected through hyperedge HE-2 (induced by source paper "the costs and benefits of ridesharing sequential individual rationality and sequential fairness"):
  with members:
    - "incentive design for ridesharing with uncertainty"

Connected through hyperedge HE-3 (induced by source paper "route planning in transportation networks"):
  with members:
    - "trip based public transit routing"
    - "optimal hub labeling is np complete"
    - "salt a unified framework for all shortest path query variants on road networks"
    - "two phase bicriterion search for finding fast and efficient electric vehicle routes"
    - "customizable contraction hierarchies"
    - "shortest path and distance queries on road networks towards bridging theory and practice"
    - "fast exact shortest path distance queries on large networks by pruned landmark labeling"
    - "distance oracles for time dependent networks"

Connected through hyperedge HE-4 (induced by source paper "design and management of vehicle sharing systems a survey of algorithmic approaches"):
  with members:
    - "dynamic vehicle redistribution and online price incentives in shared mobility systems"

Connected through hyperedge HE-5 (induced by source paper "customizable contraction hierarchies"):
  with members:
    - "graph bisection with pareto optimization"
    - "route planning in transportation networks"
    - "computing all pairs shortest paths by leveraging low treewidth"
    - "fast hierarchical clustering and other applications of dynamic closest pairs"

Connected through hyperedge HE-6 (induced by source paper "compressed transmission of route descriptions"):
  with members:
    - "defining and computing alternative routes in road networks"

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)