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: "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.

Connected through hyperedge HE-1 (induced by source paper "uniform reliability of self join free conjunctive queries"):
  with members:
    - "the shapley value of tuples in query answering"
    - "symmetric weighted first order model counting"
    - "probabilistic databases with markoviews"

Connected through hyperedge HE-2 (induced by source paper "data management for causal algorithmic fairness"):
  with members:
    - "capuchin causal database repair for algorithmic fairness"
    - "causal reasoning for algorithmic fairness"
    - "bias in olap queries detection explanation and removal"
    - "fairness testing testing software for discrimination"
    - "snorkel rapid training data creation with weak supervision"
    - "computing optimal repairs for functional dependencies"
    - "algorithmic decision making and the cost of fairness"
    - "equality of opportunity in supervised learning"

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:
    - "the shapley value of tuples in query answering"
    - "model counting for conjunctive queries without self joins"
    - "a unified approach to interpreting model predictions"
    - "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"

Connected through hyperedge HE-4 (induced by source paper "the shapley value of tuples in query answering"):
  with members:
    - "causes for query answers from databases datalog abduction view updates and integrity constraints"
    - "shapley meets shapley"
    - "the complexity of causality and responsibility for query answers and non answers"
    - "why so or why no functional causality for explaining query answers"

Connected through hyperedge HE-5 (induced by source paper "the causality repair connection in databases causality programs"):
  with members:
    - "consistency and trust in peer data exchange systems"
    - "causes for query answers from databases datalog abduction view updates and integrity constraints"
    - "achieving data privacy through secrecy views and null based virtual updates"
    - "the complexity of causality and responsibility for query answers and non answers"
    - "design and implementation of aggregate functions in the dlv system"
    - "the dlv system for knowledge representation and reasoning"
    - "responsibility and blame a structural model approach"
    - "answer sets for consistent query answering in inconsistent databases"

Connected through hyperedge HE-6 (induced by source paper "specifying and computing causes for query answers in databases via database repairs and repair programs"):
  with members:
    - "measuring and computing database inconsistency via repairs"
    - "consistency and trust in peer data exchange systems"
    - "achieving data privacy through secrecy views and null based virtual updates"
    - "the complexity of causality and responsibility for query answers and non answers"
    - "prioritized repairing and consistent query answering in relational databases"
    - "the dlv system for knowledge representation and reasoning"
    - "complexity of consistent query answering in databases under cardinality based and incremental repair semantics"
    - "minimal change integrity maintenance using tuple deletions"

Connected through hyperedge HE-7 (induced by source paper "causes for query answers from databases datalog abduction view updates and integrity constraints"):
  with members:
    - "causes for query answers from databases datalog abduction and view updates the presence of integrity constraints"
    - "query answer causality in databases abductive diagnosis and view updates"
    - "from causes for database queries to repairs and model based diagnosis and back"
    - "achieving data privacy through secrecy views and null based virtual updates"
    - "the complexity of causality and responsibility for query answers and non answers"
    - "complexity of consistent query answering in databases under cardinality based and incremental repair semantics"
    - "coherent integration of databases by abductive logic programming"
    - "responsibility and blame a structural model approach"

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)