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: "improved approximation algorithms for budgeted node weighted steiner problems"
  Abstract: Moss and Rabani[12] study constrained node-weighted Steiner tree problems with two independent weight values associated with each node, namely, cost and prize (or penalty). They give an O(log n)-approximation algorithm for the prize-collecting node-weighted Steiner tree problem (PCST). They use the algorithm for PCST to obtain a bicriteria (2, O(log n))-approximation algorithm for the Budgeted node-weighted Steiner tree problem. Their solution may cost up to twice the budget, but collects a factor Omega(1/log n) of the optimal prize. We improve these results from at least two aspects. #R##N#Our first main result is a primal-dual O(log h)-approximation algorithm for a more general problem, prize-collecting node-weighted Steiner forest, where we have (h) demands each requesting the connectivity of a pair of vertices. Our algorithm can be seen as a greedy algorithm which reduces the number of demands by choosing a structure with minimum cost-to-reduction ratio. This natural style of argument (also used by Klein and Ravi[10] and Guha et al.[8]) leads to a much simpler algorithm than that of Moss and Rabani[12] for PCST. #R##N#Our second main contribution is for the Budgeted node-weighted Steiner tree problem, which is also an improvement to [12] and [8]. In the unrooted case, we improve upon an O(log^2(n))-approximation of [8], and present an O(log n)-approximation algorithm without any budget violation. For the rooted case, where a specified vertex has to appear in the solution tree, we improve the bicriteria result of [12] to a bicriteria approximation ratio of (1+eps, O(log n)/(eps^2)) for any positive (possibly subconstant) (eps). That is, for any permissible budget violation (1+eps), we present an algorithm achieving a tradeoff in the guarantee for prize. Indeed, we show that this is almost tight for the natural linear-programming relaxation used by us as well as in [12].

Connected through hyperedge HE-1 (induced by source paper "2 node connectivity network design"):
  with members:
    - "breaching the 2 approximation barrier for connectivity augmentation a reduction to steiner tree"
    - "approximating k connected m dominating sets"
    - "improved approximation for tree augmentation saving by rewiring"
    - "approximation algorithm for minimum weight fault tolerant virtual backbone in unit disk graphs"
    - "on the tree augmentation problem"
    - "a simplified 1 5 approximation algorithm for augmenting edge connectivity of a graph from 1 to 2"
    - "nearly tight low stretch spanning trees"
    - "lower stretch spanning trees"

Connected through hyperedge HE-2 (induced by source paper "node weighted network design in planar and minor closed families of graphs"):
  with members:
    - "spider covers for prize collecting network activation problem"
    - "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-3 (induced by source paper "the parameterized hardness of the k center problem in transportation networks"):
  with members:
    - "hierarchy of transportation network parameters and hardness results"
    - "a 1 varepsilon embedding of low highway dimension graphs into bounded treewidth graphs"
    - "structural parameters tight bounds and approximation for k r center"
    - "polynomial time approximation schemes for k center and bounded capacity vehicle routing in metrics with bounded highway dimension"
    - "the limited blessing of low dimensionality when 1 1 d is the best possible exponent for d dimensional geometric problems"
    - "fixed parameter approximations for k center problems in low highway dimension graphs"
    - "optimal parameterized algorithms for planar facility location problems using voronoi diagrams"
    - "analytical approach to parallel repetition"

Connected through hyperedge HE-4 (induced by source paper "the complexity landscape of fixed parameter directed steiner network problems"):
  with members:
    - "on directed steiner trees with multiple roots"
    - "a polynomial time approximation scheme for euclidean steiner forest"
    - "euclidean prize collecting steiner forest"
    - "approximation schemes for steiner forest on planar graphs and graphs of bounded treewidth"

Connected through hyperedge HE-5 (induced by source paper "approximating node weighted k mst on planar graphs"):
  with members:
    - "node weighted network design in planar and minor closed families of graphs"
    - "approximation algorithms for node weighted prize collecting steiner tree problems on planar graphs"
    - "an lmp o log n approximation algorithm for node weighted prize collecting steiner tree"
    - "lagrangian relaxation and partial cover"

Connected through hyperedge HE-6 (induced by source paper "covering problems in edge and node weighted graphs"):
  with members:
    - "an lmp o log n approximation algorithm for node weighted prize collecting steiner tree"
    - "spider covers for prize collecting network activation problem"

Connected through hyperedge HE-7 (induced by source paper "spider covers for prize collecting network activation problem"):
  with members:
    - "covering problems in edge and node weighted graphs"
    - "an lmp o log n approximation algorithm for node weighted prize collecting steiner tree"
    - "approximating subset k connectivity problems"
    - "an o k 3 log n approximation algorithm for vertex connectivity survivable network design"

Connected through hyperedge HE-8 (induced by source paper "analyzing the optimal neighborhood algorithms for budgeted and partial connected dominating set problems"):
  with members:
    - "the power of local information in social networks"
    - "online myopic network covering"
    - "scheduling with outliers"

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)