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: "fair allocation of indivisible goods improvement and generalization"
  Abstract: We study the problem of fair allocation for indivisible goods. We use the the maxmin share paradigm introduced by Budish as a measure for fairness. Procacciafirst (EC'14) were first to investigate this fundamental problem in the additive setting. In contrast to what real-world experiments suggest, they show that a maxmin guarantee (1-$\MMS$ allocation) is not always possible even when the number of agents is limited to 3. While the existence of an approximation solution (e.g. a $1/2$-$\MMS$ allocation) is quite straightforward, improving the guarantee becomes subtler for larger constants. Procaccia provide a proof for existence of a $2/3$-$\MMS$ allocation and leave the question open for better guarantees. #R##N#Our main contribution is an answer to the above question. We improve the result of \procacciafirst\! to a $3/4$ factor in the additive setting. The main idea for our $3/4$-$\MMS$ allocation method is clustering the agents. To this end, we introduce three notions and techniques, namely reducibility, matching allocation, and cycle-envy-freeness, and prove the approximation guarantee of our algorithm via non-trivial applications of these techniques. Our analysis involves coloring and double counting arguments that might be of independent interest. #R##N#One major shortcoming of the current studies on fair allocation is the additivity assumption on the valuations. We alleviate this by extending our results to the case of submodular, fractionally subadditive, and subadditive settings. More precisely, we give constant approximation guarantees for submodular and XOS agents, and a logarithmic approximation for the case of subadditive agents. Furthermore, we complement our results by providing close upper bounds for each class of valuation functions. Finally, we present algorithms to find such allocations for additive, submodular, and XOS settings in polynomial time.

Connected through hyperedge HE-1 (induced by source paper "an improved approximation algorithm for maximin shares"):
  with members:
    - "fair division of indivisible goods among strategic agents"
    - "a little charity guarantees almost envy freeness"
    - "maximin share allocations on cycles"
    - "connected fair allocation of indivisible goods"
    - "an algorithmic framework for approximating maximin share allocation of chores"
    - "the fair division of hereditary set systems"
    - "fair allocation of indivisible goods to asymmetric agents"
    - "groupwise maximin fair allocation of indivisible goods"

Connected through hyperedge HE-2 (induced by source paper "fair division under cardinality constraints"):
  with members:
    - "groupwise maximin fair allocation of indivisible goods"
    - "approximation algorithms for computing maximin share allocations"
    - "fair division of a graph"

Connected through hyperedge HE-3 (induced by source paper "approximation algorithms for maximin fair division"):
  with members:
    - "approximation algorithms for computing maximin share allocations"
    - "approximation algorithms for max min share allocations of indivisible chores and goods"
    - "efficiency and sequenceability in fair division of indivisible goods with additive preferences"
    - "symmetry and approximability of submodular maximization problems"
    - "on allocating goods to maximize fairness"

Connected through hyperedge HE-4 (induced by source paper "groupwise maximin fair allocation of indivisible goods"):
  with members:
    - "approximation algorithms for computing maximin share allocations"
    - "fair division of a graph"
    - "approximation algorithms for max min share allocations of indivisible chores and goods"

Connected through hyperedge HE-5 (induced by source paper "fair allocation of indivisible goods to asymmetric agents"):
  with members:
    - "competitive equilibria with indivisible goods and generic budgets"
    - "approximation algorithms for computing maximin share allocations"

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)