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: "parameterized power vertex cover"
  Abstract: We study a recently introduced generalization of the Vertex Cover (VC) problem, called Power Vertex Cover (PVC). In this problem, each edge of the input graph is supplied with a positive integer demand. A solution is an assignment of (power) values to the vertices, so that for each edge one of its endpoints has value as high as the demand, and the total sum of power values assigned is minimized. We investigate how this generalization affects the parameterized complexity of Vertex Cover. On the positive side, when parameterized by the value of the optimal P, we give an O*(1.274^P)-time branching algorithm (O* is used to hide factors polynomial in the input size), and also an O*(1.325^P)-time algorithm for the more general asymmetric case of the problem, where the demand of each edge may differ for its two endpoints. When the parameter is the number of vertices k that receive positive value, we give O*(1.619^k) and O*(k^k)-time algorithms for the symmetric and asymmetric cases respectively, as well as a simple quadratic kernel for the asymmetric case. We also show that PVC becomes significantly harder than classical VC when parameterized by the graph's treewidth t. More specifically, we prove that unless the ETH is false, there is no n^o(t)-time algorithm for PVC. We give a method to overcome this hardness by designing an FPT approximation scheme which gives a (1+epsilon)-approximation to the optimal solution in time FPT in parameters t and 1/epsilon.

Connected through hyperedge HE-1 (induced by source paper "polynomial time data reduction for weighted problems beyond additive goal functions"):
  with members:
    - "parameterized algorithms and data reduction for the short secluded s t path problem"
    - "fixed parameter algorithms for maximum profit facility location under matroid constraints"
    - "on approximate data reduction for the rural postman problem theory and experiments"
    - "fair knapsack"
    - "a parameterized approximation algorithm for the mixed and windy capacitated arc routing problem theory and experiments"
    - "parameterized algorithms for power efficient connected symmetric wireless sensor networks"
    - "new algorithms for minimizing the weighted number of tardy jobs on a single machine"
    - "interval scheduling and colorful independent sets"

Connected through hyperedge HE-2 (induced by source paper "structural parameters tight bounds and approximation for k r center"):
  with members:
    - "parameterized approximation algorithms for some location problems in graphs"
    - "fixed parameter approximations for k center problems in low highway dimension graphs"
    - "optimal dynamic program for r domination problems over tree decompositions"
    - "faster algorithms for vertex partitioning problems parameterized by clique width"
    - "parameterized edge hamiltonicity"
    - "parameterized approximation schemes using graph widths"
    - "known algorithms on graphs of bounded treewidth are probably optimal"

Connected through hyperedge HE-3 (induced by source paper "structurally parameterized d scattered set"):
  with members:
    - "structural parameters tight bounds and approximation for k r center"
    - "on distance d independent set and other problems in graphs with few minimal separators"
    - "optimal parameterized algorithms for planar facility location problems using voronoi diagrams"
    - "optimal dynamic program for r domination problems over tree decompositions"
    - "parameterized approximation schemes using graph widths"
    - "known algorithms on graphs of bounded treewidth are probably optimal"

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)