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 regret bounded vehicle routing and applications to distance constrained vehicle routing"
  Abstract: We consider vehicle-routing problems (VRPs) that incorporate the notion of {\em regret} of a client, which is a measure of the waiting time of a client relative to its shortest-path distance from the depot. Formally, we consider both the additive and multiplicative versions of, what we call, the {\em regret-bounded vehicle routing problem} (RVRP). In these problems, we are given an undirected complete graph $G=(\{r\}\cup V,E)$ on $n$ nodes with a distinguished root (depot) node $r$, edge costs $\{c_{uv}\}$ that form a metric, and a regret bound $R$. Given a path $P$ rooted at $r$ and a node $v\in P$, let $c_P(v)$ be the distance from $r$ to $v$ along $P$. The goal is to find the fewest number of paths rooted at $r$ that cover all the nodes so that for every node $v$ covered by (say) path $P$: (i) its additive regret $c_P(v)-c_{rv}$, with respect to $P$ is at most $R$ in {\em additive-RVRP}; or (ii) its multiplicative regret, $c_P(c)/c_{rv}$, with respect to $P$ is at most $R$ in {\em multiplicative-RVRP}. #R##N#Our main result is the {\em first} constant-factor approximation algorithm for additive-RVRP by devising rounding techniques for a natural {\em configuration-style LP}. This is a substantial improvement over the previous-best $O(\log n)$-approximation. Additive-RVRP turns out be a rather central vehicle-routing problem, whose study reveals insights into a variety of other regret-related problems as well as the classical {\em distance-constrained VRP} ({DVRP}). We obtain approximation ratios of $O\bigl(\log(\frac{R}{R-1})\bigr)$ for multiplicative-RVRP, and $O\bigl(\min\bigl\{\mathit{OPT},\frac{\log D}{\log\log D}\bigr\}\bigr)$ for DVRP with distance bound $D$ via reductions to additive-RVRP; the latter improves upon the previous-best approximation for DVRP.

Connected through hyperedge HE-1 (induced by source paper "a constant factor approximation for directed latency in quasi polynomial time"):
  with members:
    - "the asymmetric traveling salesman path lp has constant integrality ratio"
    - "a constant factor approximation algorithm for the asymmetric traveling salesman problem"
    - "compact provably good lps for orienteering and regret bounded vehicle routing"
    - "an improved integrality gap for asymmetric tsp paths"
    - "improving christofides algorithm for the s t path tsp"
    - "asymmetric traveling salesman path and directed latency problems"

Connected through hyperedge HE-2 (induced by source paper "vehicle routing with subtours"):
  with members:
    - "new inapproximability bounds for tsp"
    - "balancing minimum spanning trees and shortest path trees"

Connected through hyperedge HE-3 (induced by source paper "a framework for vehicle routing approximation schemes in trees"):
  with members:
    - "a tight 4 3 approximation for capacitated vehicle routing in trees"
    - "compact provably good lps for orienteering and regret bounded vehicle routing"

Connected through hyperedge HE-4 (induced by source paper "compact provably good lps for orienteering and regret bounded vehicle routing"):
  with members:
    - "an improved integrality gap for asymmetric tsp paths"
    - "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)