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: "polynomial time approximation schemes for the traveling repairman and other minimum latency problems"
  Abstract: We give a polynomial time, $(1+\epsilon)$-approximation algorithm for the traveling repairman problem (TRP) in the Euclidean plane and on weighted trees. This improves on the known quasi-polynomial time approximation schemes for these problems. The algorithm is based on a simple technique that reduces the TRP to what we call the \emph{segmented TSP}. Here, we are given numbers $l_1,\dots,l_K$ and $n_1,\dots,n_K$ and we need to find a path that visits at least $n_h$ points within path distance $l_h$ from the starting point for all $h\in\{1,\dots,K\}$. A solution is $\alpha$-approximate if at least $n_h$ points are visited within distance $\alpha l_h$. It is shown that any algorithm that is $\alpha$-approximate for \emph{every constant} $K$ in some metric space, gives an $\alpha(1+\epsilon)$-approximation for the TRP in the same metric space. Subsequently, approximation schemes are given for this segmented TSP problem in the plane and on weighted trees. The segmented TSP with only one segment ($K=1$) is equivalent to the $k$-TSP for which a $(2+\epsilon)$-approximation is known for a general metric space. Hence, this approach through the segmented TSP gives new impulse for improving on the 3.59-approximation for TRP in a general metric space. A similar reduction applies to many other minimum latency problems. To illustrate the strength of this approach we apply it to the well-studied scheduling problem of minimizing total weighted completion time under precedence constraints, $1|prec|\sum w_{j}C_{j}$, and present a polynomial time approximation scheme for the case of interval order precedence constraints. This improves on the known $3/2$-approximation for this problem. Both approximation schemes apply as well if release dates are added to the problem.

Connected through hyperedge HE-1 (induced by source paper "minimizing latency in online ride and delivery services"):
  with members:
    - "linear programming based approximation algorithms for multi vehicle minimum latency problems"

Connected through hyperedge HE-2 (induced by source paper "a 2 epsilon approximation for precedence constrained single machine scheduling with release dates and total weighted completion time objective"):
  with members:
    - "a 2 542 approximation for precedence constrained single machine scheduling with release dates and total weighted completion time objective"

Connected through hyperedge HE-3 (induced by source paper "a polynomial time approximation scheme for the airplane refueling problem"):
  with members:
    - "a primal dual approximation algorithm for min sum single machine scheduling problems"
    - "how unsplittable flow covering helps scheduling with job dependent cost functions"
    - "dual techniques for scheduling on a machine with varying speed"
    - "the geometry of scheduling"

Connected through hyperedge HE-4 (induced by source paper "linear programming based approximation algorithms for multi vehicle minimum latency problems"):
  with members:
    - "facility location with client latencies linear programming based techniques for minimum latency 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)