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 "quantifying causal effects on query answering in databases"):
  Abstract: The notion of actual causation, as formalized by Halpern and Pearl, has been recently applied to relational databases, to characterize and compute actual causes for possibly unexpected answers to monotone queries. Causes take the form of database tuples, and can be ranked according to their causal responsibility, a numerical measure of their relevance as a cause to the query answer. In this work we revisit this notion, introducing and making a case for an alternative measure of causal contribution, that of causal effect. The measure generalizes actual causes, and can be applied beyond monotone queries. We show that causal effect provides intuitive and intended results.

Includes members:
  Member "causes for query answers from databases datalog abduction and view updates the presence of integrity constraints":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "causes for query answers from databases datalog abduction view updates and integrity constraints")
  Member "query answer causality in databases abductive diagnosis and view updates":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "causes for query answers from databases datalog abduction view updates and integrity constraints")
  Member "from causes for database queries to repairs and model based diagnosis and back":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "data management for causal algorithmic fairness")
  Member "the complexity of causality and responsibility for query answers and non answers":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "causality based explanation of classification outcomes")
  Member "causality and the semantics of provenance":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a core calculus for provenance")
  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.DB(Databases)