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: "stackelberg network pricing games"
  Abstract: We study a multi-player one-round game termed Stackelberg Network Pricing Game, in which a leader can set prices for a subset of $m$ priceable edges in a graph. The other edges have a fixed cost. Based on the leader's decision one or more followers optimize a polynomial-time solvable combinatorial minimization problem and choose a minimum cost solution satisfying their requirements based on the fixed costs and the leader's prices. The leader receives as revenue the total amount of prices paid by the followers for priceable edges in their solutions, and the problem is to find revenue maximizing prices. Our model extends several known pricing problems, including single-minded and unit-demand pricing, as well as Stackelberg pricing for certain follower problems like shortest path or minimum spanning tree. Our first main result is a tight analysis of a single-price algorithm for the single follower game, which provides a $(1+\epsilon) \log m$-approximation for any $\epsilon >0$. This can be extended to provide a $(1+\epsilon)(\log k + \log m)$-approximation for the general problem and $k$ followers. The latter result is essentially best possible, as the problem is shown to be hard to approximate within $\mathcal{O(\log^\epsilon k + \log^\epsilon m)$. If followers have demands, the single-price algorithm provides a $(1+\epsilon)m^2$-approximation, and the problem is hard to approximate within $\mathcal{O(m^\epsilon)$ for some $\epsilon >0$. Our second main result is a polynomial time algorithm for revenue maximization in the special case of Stackelberg bipartite vertex cover, which is based on non-trivial max-flow and LP-duality techniques. Our results can be extended to provide constant-factor approximations for any constant number of followers.

Connected through hyperedge HE-1 (induced by source paper "negative prices in network pricing games"):
  with members:
    - "toll caps in privatized road networks"
    - "inefficiencies in network models a graph theoretic perspective"
    - "approximate revenue maximization with multiple items"
    - "matroids are immune to braess paradox"
    - "new complexity results and algorithms for the minimum tollbooth problem"
    - "stackelberg shortest path tree game revisited"
    - "the stackelberg minimum spanning tree game"
    - "stackelberg network pricing is hard to approximate"

Connected through hyperedge HE-2 (induced by source paper "toll caps in privatized road networks"):
  with members:
    - "the impact of worst case deviations in non atomic network routing games"
    - "efficiency and complexity of price competition among single product vendors"
    - "strategic decentralization in binary choice composite congestion games"
    - "price competition in networked markets how do monopolies impact social welfare"

Connected through hyperedge HE-3 (induced by source paper "network investment game with wardrop followers"):
  with members:
    - "toll caps in privatized road networks"
    - "computing equilibria in atomic splittable polymatroid congestion games with convex costs"
    - "the stackelberg minimum spanning tree game"

Connected through hyperedge HE-4 (induced by source paper "specializations and generalizations of the stackelberg minimum spanning tree game"):
  with members:
    - "the stackelberg minimum spanning tree game on planar and bounded treewidth graphs"
    - "the stackelberg minimum spanning tree game"
    - "stackelberg network pricing is hard to approximate"
    - "improved hardness of approximation for stackelberg shortest path pricing"

Connected through hyperedge HE-5 (induced by source paper "the stackelberg minimum spanning tree game on planar and bounded treewidth graphs"):
  with members:
    - "specializations and generalizations of the stackelberg minimum spanning tree game"
    - "the stackelberg minimum spanning tree game"
    - "improved hardness of approximation for stackelberg shortest path pricing"
    - "an approximation algorithm for stackelberg network pricing"

Connected through hyperedge HE-6 (induced by source paper "stackelberg shortest path tree game revisited"):
  with members:
    - "the stackelberg minimum spanning tree game"
    - "stackelberg network pricing is hard to approximate"
    - "improved hardness of approximation for stackelberg shortest path pricing"

Connected through hyperedge HE-7 (induced by source paper "graph products revisited tight approximation hardness of induced matching poset dimension and more"):
  with members:
    - "minimizing flow time in the wireless gathering problem"

Connected through hyperedge HE-8 (induced by source paper "welfare and profit maximization with production costs"):
  with members:
    - "dynamic and non uniform pricing strategies for revenue maximization"
    - "combinatorial auctions with decreasing marginal utilities"

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)