human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "truthful mechanisms for matching and clustering in an ordinal world"):
  Abstract: We study truthful mechanisms for matching and related problems in a partial information setting, where the agents' true utilities are hidden, and the algorithm only has access to ordinal preference information. Our model is motivated by the fact that in many settings, agents cannot express the numerical values of their utility for different outcomes, but are still able to rank the outcomes in their order of preference. Specifically, we study problems where the ground truth exists in the form of a weighted graph of agent utilities, but the algorithm can only elicit the agents' private information in the form of a preference ordering for each agent induced by the underlying weights. Against this backdrop, we design truthful algorithms to approximate the true optimum solution with respect to the hidden weights. Our techniques yield universally truthful algorithms for a number of graph problems: a 1.76-approximation algorithm for Max-Weight Matching, 2-approximation algorithm for Max k-matching, a 6-approximation algorithm for Densest k-subgraph, and a 2-approximation algorithm for Max Traveling Salesman as long as the hidden weights constitute a metric. We also provide improved approximation algorithms for such problems when the agents are not able to lie about their preferences. Our results are the first non-trivial truthful approximation algorithms for these problems, and indicate that in many situations, we can design robust algorithms even when the agents may lie and only provide ordinal information instead of precise utilities.

Includes members:
  Member "size versus truthfulness in the house allocation problem":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "tradeoffs between information and ordinal approximation for bipartite matching")
  Member "on truthful mechanisms for maximin share allocations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fair and truthful mechanisms for dichotomous valuations")
  Member "truthful facility assignment with resource augmentation an exact analysis of serial dictatorship":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "social cost guarantees in smart route guidance")
  Member "randomized social choice functions under metric preferences":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "how good is a two party election game")
  Member "on voting and facility location":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "selecting voting locations for fun and profit")
  Member "social welfare in one sided matchings random priority and beyond":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "keeping your friends close land allocation with friends")
  Member "social welfare in one sided matching markets without money":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "bounded incentives in manipulating the probabilistic serial rule")
  Member "truthful assignment without money":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "bounded incentives in manipulating the probabilistic serial rule")

Question: Please tell me which class the source paper 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)