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: "trip based public transit routing"
  Abstract: We study the problem of computing all Pareto-optimal journeys in a public transit network regarding the two criteria of arrival time and number of transfers taken. We take a novel approach, focusing on trips and transfers between them, allowing fine-grained modeling. Our experiments on the metropolitan network of London show that the algorithm computes full 24-hour profiles in 70ms after a preprocessing phase of 30s, allowing fast queries in dynamic scenarios.

Connected through hyperedge HE-1 (induced by source paper "unlimited transfers for multi modal route planning an efficient solution"):
  with members:
    - "fast public transit routing with unrestricted walking through hub labeling"
    - "shortest feasible paths with charging stops for battery electric vehicles"
    - "connection scan algorithm"
    - "public transit labeling"
    - "route planning in transportation networks"

Connected through hyperedge HE-2 (induced by source paper "efficient computation of multi modal public transit traffic assignments using ultra"):
  with members:
    - "unlimited transfers for multi modal route planning an efficient solution"
    - "fast public transit routing with unrestricted walking through hub labeling"
    - "trip based public transit routing using condensed search trees"
    - "route planning in transportation networks"

Connected through hyperedge HE-3 (induced by source paper "connection scan algorithm"):
  with members:
    - "trip based public transit routing using condensed search trees"
    - "public transit labeling"
    - "route planning in transportation networks"
    - "contraction of timetable networks with realistic transfers"

Connected through hyperedge HE-4 (induced by source paper "trip based public transit routing using condensed search trees"):
  with members:
    - "public transit labeling"
    - "contraction of timetable networks with realistic transfers"

Connected through hyperedge HE-5 (induced by source paper "route planning in transportation networks"):
  with members:
    - "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"
    - "transit node routing reconsidered"

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)