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: "approximation algorithms for orienteering with time windows"
  Abstract: Orienteering is the following optimization problem: given an edge-weighted graph (directed or undirected), two nodes s,t and a time limit T, find an s-t walk of total length at most T that maximizes the number of distinct nodes visited by the walk. One obtains a generalization, namely orienteering with time-windows (also referred to as TSP with time-windows), if each node v has a specified time-window [R(v), D(v)] and a node v is counted as visited by the walk only if v is visited during its time-window. For the time-window problem, an O(\log \opt) approximation can be achieved even for directed graphs if the algorithm is allowed quasi-polynomial time. However, the best known polynomial time approximation ratios are O(\log^2 \opt) for undirected graphs and O(\log^4 \opt) in directed graphs. In this paper we make some progress towards closing this discrepancy, and in the process obtain improved approximation ratios in several natural settings. Let L(v) = D(v) - R(v) denote the length of the time-window for v and let \lmax = \max_v L(v) and \lmin = \min_v L(v). Our results are given below with \alpha denoting the known approximation ratio for orienteering (without time-windows). Currently \alpha = (2+\eps) for undirected graphs and \alpha = O(\log^2 \opt) in directed graphs. #R##N#1. An O(\alpha \log \lmax) approximation when R(v) and D(v) are integer valued for each v. #R##N#2. An O(\alpha \max{\log \opt, \log \frac{\lmax}{\lmin}}) approximation. #R##N#3. An O(\alpha \log \frac{\lmax}{\lmin}) approximation when no start and end points are specified. #R##N#In particular, if \frac{\lmax}{\lmin} is poly-bounded, we obtain an O(\log n) approximation for the time-window problem in undirected graphs.

Connected through hyperedge HE-1 (induced by source paper "online service with delay"):
  with members:
    - "online matching haste makes waste"
    - "tsp with time windows and service time"
    - "an optimal randomized online algorithm for reordering buffer management"
    - "a bicriteria approximation for the reordering buffer problem"
    - "the k server dual and loose competitiveness for paging"
    - "competitive paging algorithms"

Connected through hyperedge HE-2 (induced by source paper "speedup in the traveling repairman problem with constrained time windows"):
  with members:
    - "speedup in the traveling repairman problem with unit time windows"
    - "approximation algorithms for the traveling repairman and speeding deliveryman problems"

Connected through hyperedge HE-3 (induced by source paper "approximation algorithms for the traveling repairman and speeding deliveryman problems"):
  with members:
    - "two multivehicle routing problems with unit time windows"
    - "speedup in the traveling repairman problem with constrained time windows"
    - "speedup in the traveling repairman problem with unit time windows"

Connected through hyperedge HE-4 (induced by source paper "speedup in the traveling repairman problem with unit time windows"):
  with members:
    - "approximation algorithms for the traveling repairman and speeding deliveryman problems"

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)