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 "influence in classification via cooperative game theory"):
  Abstract: A dataset has been classified by some unknown classifier into two types of points. What were the most important factors in determining the classification outcome? In this work, we employ an axiomatic approach in order to uniquely characterize an influence measure: a function that, given a set of classified points, outputs a value for each feature corresponding to its influence in determining the classification outcome. We show that our influence measure takes on an intuitive form when the unknown classifier is linear. Finally, we employ our influence measure in order to analyze the effects of user profiling on Google's online display advertising.

Includes members:
  Member "a methodology for information flow experiments":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the accuracy of the demographic inferences shown on google s ad settings")
  Member "automated experiments on ad privacy settings a tale of opacity choice and discrimination":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "artificial intelligent ethics in the digital era an engineering ethical framework proposal")
  Member "probabilities of causation bounds and identification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "counterfactual off policy evaluation with gumbel max structural causal models")
  Member "fairness through awareness":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "algorithmic fairness")
  Member "cooperative games with overlapping coalitions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "dynamic network slicing for scalable fog computing systems with energy harvesting")
  Member "responsibility and blame a structural model approach":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "causality based explanation of classification outcomes")

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)