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: "spider covers for prize collecting network activation problem"
  Abstract: In the network activation problem, each edge in a graph is associated with an activation function, that decides whether the edge is activated from node-weights assigned to its end-nodes. The feasible solutions of the problem are the node-weights such that the activated edges form graphs of required connectivity, and the objective is to find a feasible solution minimizing its total weight. In this paper, we consider a prize-collecting version of the network activation problem, and present first non- trivial approximation algorithms. Our algorithms are based on a new LP relaxation of the problem. They round optimal solutions for the relaxation by repeatedly computing node-weights activating subgraphs called spiders, which are known to be useful for approximating the network activation problem.

Connected through hyperedge HE-1 (induced by source paper "node weighted network design in planar and minor closed families of graphs"):
  with members:
    - "improved approximation algorithms for budgeted node weighted steiner problems"
    - "an improved approximation algorithm for the minimum cost subset k connected subgraph problem"
    - "approximation schemes for steiner forest on planar graphs and graphs of bounded treewidth"
    - "an o k 3 log n approximation algorithm for vertex connectivity survivable network design"

Connected through hyperedge HE-2 (induced by source paper "improved approximation algorithms for k connected m dominating set problems"):
  with members:
    - "approximation algorithm for minimum weight fault tolerant virtual backbone in unit disk graphs"
    - "constant approximation algorithms for highly connected multi dominating sets in unit disk graphs"
    - "parameters of two prover one round game and the hardness of connectivity problems"
    - "an improved approximation algorithm for the minimum cost subset k connected subgraph problem"
    - "approximating subset k connectivity problems"

Connected through hyperedge HE-3 (induced by source paper "a note on the survivable network design problem"):
  with members:
    - "node weighted network design in planar and minor closed families of graphs"

Connected through hyperedge HE-4 (induced by source paper "constant approximation algorithms for highly connected multi dominating sets in unit disk graphs"):
  with members:
    - "approximation algorithm for minimum weight fault tolerant virtual backbone in unit disk graphs"
    - "latency bounded target set selection in social networks"
    - "on the approximability and exact algorithms for vector domination and related problems in graphs"

Connected through hyperedge HE-5 (induced by source paper "covering problems in edge and node weighted graphs"):
  with members:
    - "improved approximation algorithms for budgeted node weighted steiner problems"
    - "an lmp o log n approximation algorithm for node weighted prize collecting steiner tree"

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)