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: "reaping the benefits of bundling under high production costs"
  Abstract: It has long been known in the economics literature that selling different goods in a single bundle can significantly increase revenue, even when the valuations for the goods are independent. However, bundling is no longer profitable if the goods have high production costs. To overcome this issue, we introduce Pure Bundling with Disposal for Cost (PBDC), where after buying the bundle, we allow the customer to return any subset of items for their production cost. We demonstrate using classical examples that PBDC captures the concentration effects of bundling while allowing for the flexibility of individual sales, extracting all of the consumer welfare in situations where previous simple mechanisms could not.Furthermore, we prove a theoretical guarantee on the performance of PBDC that holds for arbitrary independent distributions, using techniques from the mechanism design literature. We transform the problem with costs to a problem with negative valuations, extend the mechanism design techniques to negative valuations, and use the Core-Tail decomposition of Babaioff et al. from [BILW14] to show that either PBDC or individual sales will obtain at least 1/5.2 of the optimal profit. This also improves the bound of 1/6 from [BILW14]. We advance the upper bound as well, constructing two IID items with zero cost where mixed bundling earns 1.19 more revenue than either pure bundling or individual sales.Our numerical experiments show that PBDC outperforms all other simple pricing schemes, including the Bundle-Size Pricing (BSP) introduced by Chu et al. in [CLS11], under the same families of distributions used in [CLS11]. We also provide the first theoretical explanation for some of the great experimental successes in [CLS11]. All in all, our work shows establishes PBDC as a robust, computationally-minimal heuristic that is easy to market to the customer.

Connected through hyperedge HE-1 (induced by source paper "simple and approximately optimal pricing for proportional complementarities"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "approximating gains from trade in two sided markets via simple mechanisms"
    - "on the competition complexity of dynamic mechanism design"
    - "the value of information concealment"
    - "simple mechanisms for subadditive buyers via duality"
    - "mechanism design for subadditive agents via an ex ante relaxation"
    - "simple mechanisms for a subadditive buyer and applications to revenue monotonicity"
    - "a simple and approximately optimal mechanism for an additive buyer"

Connected through hyperedge HE-2 (induced by source paper "99 revenue via enhanced competition"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "approximate revenue maximization with multiple items"
    - "on the competition complexity of dynamic mechanism design"
    - "on revenue monotonicity in combinatorial auctions"
    - "simple mechanisms for subadditive buyers via duality"
    - "the competition complexity of auctions a bulow klemperer result for multi dimensional bidders"
    - "mechanism design for subadditive agents via an ex ante relaxation"
    - "on the computational complexity of optimal simple mechanisms"

Connected through hyperedge HE-3 (induced by source paper "simple mechanisms for a subadditive buyer and applications to revenue monotonicity"):
  with members:
    - "a duality based unified approach to bayesian mechanism design"
    - "approximate revenue maximization with multiple items"
    - "simple mechanisms for subadditive buyers via duality"
    - "combinatorial prophet inequalities"
    - "a simple and approximately optimal mechanism for a buyer with complements"
    - "mechanism design for subadditive agents via an ex ante relaxation"
    - "on the computational complexity of optimal simple mechanisms"
    - "a simple and approximately optimal mechanism for an additive buyer"

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.GT(Computer Science and Game Theory)