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: "public transit labeling"
  Abstract: We study the journey planning problem in public transit networks. Developing efficient preprocessing-based speedup techniques for this problem has been challenging: current approaches either require massive preprocessing effort or provide limited speedups. Leveraging recent advances in Hub Labeling, the fastest algorithm for road networks, we revisit the well-known time-expanded model for public transit. Exploiting domain-specific properties, we provide simple and efficient algorithms for the earliest arrival, profile, and multicriteria problems, with queries that are orders of magnitude faster than the state of the art.

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"
    - "trip based public transit routing"
    - "route planning in transportation networks"

Connected through hyperedge HE-2 (induced by source paper "fast public transit routing with unrestricted walking through hub labeling"):
  with members:
    - "connection scan algorithm"
    - "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"
    - "trip based public transit routing"
    - "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:
    - "trip based public transit routing"
    - "contraction of timetable networks with realistic transfers"

Connected through hyperedge HE-5 (induced by source paper "rehub extending hub labels for reverse k nearest neighbor queries on large scale networks"):
  with members:
    - "route planning in transportation networks"
    - "hop doubling label indexing for point to point distance querying on scale free networks"
    - "salt a unified framework for all shortest path query variants on road networks"
    - "fast exact shortest path distance queries on large networks by pruned landmark labeling"
    - "defining and evaluating network communities based on ground truth"
    - "community structure in large networks natural cluster sizes and the absence of large well defined clusters"

Connected through hyperedge HE-6 (induced by source paper "trip based public transit routing"):
  with members:
    - "route planning in transportation networks"
    - "contraction of timetable networks with realistic transfers"

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)