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: "balancing minimum spanning trees and shortest path trees"
  Abstract: We give a simple algorithm to find a spanning tree that simultaneously approximates a shortest-path tree and a minimum spanning tree. The algorithm provides a continuous tradeoff: given the two trees and aź>0, the algorithm returns a spanning tree in which the distance between any vertex and the root of the shortest-path tree is at most 1+ź2ź times the shortest-path distance, and yet the total weight of the tree is at most 1+ź2/ź times the weight of a minimum spanning tree. Our algorithm runs in linear time and obtains the best-possible tradeoff. It can be implemented on a CREW PRAM to run a logarithmic time using one processor per vertex.

Connected through hyperedge HE-1 (induced by source paper "distributed construction of light networks"):
  with members:
    - "light spanners for high dimensional norms via stochastic decompositions"
    - "greedy spanners are optimal in doubling metrics"
    - "distributed exact shortest paths in sublinear time"
    - "improved distributed algorithms for exact shortest paths"
    - "a simple deterministic distributed mst algorithm with near optimal time and message complexities"
    - "constructing light spanners deterministically in near linear time"
    - "minor free graphs have light spanners"
    - "the greedy spanner is existentially optimal"

Connected through hyperedge HE-2 (induced by source paper "electrical flows over spanning trees"):
  with members:
    - "graph sparsification spectral sketches and faster resistance computation via short cycle decompositions"
    - "solving directed laplacian systems in nearly linear time through sparse lu factorizations"
    - "sampling random spanning trees faster than matrix multiplication"
    - "computing maximum flow with augmenting electrical flows"
    - "effective resistance reducing flows spectrally thin trees and asymmetric tsp"
    - "a simple combinatorial algorithm for solving sdd systems in nearly linear time"
    - "electrical flows laplacian systems and faster approximation of maximum flow in undirected graphs"
    - "graph sparsification by effective resistances"

Connected through hyperedge HE-3 (induced by source paper "vehicle routing with subtours"):
  with members:
    - "new inapproximability bounds for tsp"
    - "approximation algorithms for regret bounded vehicle routing and applications to distance constrained vehicle routing"

Connected through hyperedge HE-4 (induced by source paper "last but not least online spanners for buy at bulk"):
  with members:
    - "online network design algorithms via hierarchical decompositions"

Connected through hyperedge HE-5 (induced by source paper "the minimum wiener connector problem"):
  with members:
    - "identifying high betweenness centrality nodes in large social networks"
    - "fast and exact top k search for random walk with restart"
    - "defining and evaluating network communities based on ground truth"
    - "nearly linear time algorithms for graph partitioning graph sparsification and solving linear systems"

Connected through hyperedge HE-6 (induced by source paper "principles of dataset versioning exploring the recreation storage tradeoff"):
  with members:
    - "datahub collaborative data science dataset version management at scale"
    - "efficient snapshot retrieval over historical graph data"

Connected through hyperedge HE-7 (induced by source paper "a parameterized approximation algorithm for the shallow light steiner tree problem"):
  with members:
    - "improved approximation algorithms for computing k disjoint paths subject to two constraints"

Connected through hyperedge HE-8 (induced by source paper "capacitated vehicle routing with non uniform speeds"):
  with members:
    - "a quasi polynomial time approximation scheme for euclidean capacitated vehicle routing"

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)