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: "the shapley value of tuples in query answering"
  Abstract: We investigate the application of the Shapley value to quantifying the contribution of a tuple to a query answer. The Shapley value is a widely known numerical measure in cooperative game theory and in many applications of game theory for assessing the contribution of a player to a coalition game. It has been established already in the 1950s, and is theoretically justified by being the very single wealth-distribution measure that satisfies some natural axioms. While this value has been investigated in several areas, it received little attention in data management. We study this measure in the context of conjunctive and aggregate queries by defining corresponding coalition games. We provide algorithmic and complexity-theoretic results on the computation of Shapley-based contributions to query answers; and for the hard cases we present approximation algorithms.

Connected through hyperedge HE-1 (induced by source paper "causality based explanation of classification outcomes"):
  with members:
    - "explaining classifiers with causal concept effect cace"
    - "explainable ai for trees from local explanations to global understanding"
    - "an interpretable model with globally consistent explanations for credit risk"
    - "a unified approach to interpreting model predictions"
    - "the mythos of model interpretability"
    - "why should i trust you explaining the predictions of any classifier"
    - "the complexity of causality and responsibility for query answers and non answers"
    - "responsibility and blame a structural model approach"

Connected through hyperedge HE-2 (induced by source paper "uniform reliability of self join free conjunctive queries"):
  with members:
    - "quantifying causal effects on query answering in databases"
    - "symmetric weighted first order model counting"
    - "probabilistic databases with markoviews"

Connected through hyperedge HE-3 (induced by source paper "the impact of negation on the complexity of the shapley value in conjunctive queries"):
  with members:
    - "model counting for conjunctive queries without self joins"
    - "a unified approach to interpreting model predictions"
    - "quantifying causal effects on query answering in databases"
    - "causes for query answers from databases datalog abduction view updates and integrity constraints"
    - "the complexity of causality and responsibility for query answers and non answers"

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.DB(Databases)