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: "coherent integration of databases by abductive logic programming"
  Abstract: We introduce an abductive method for a coherent integration of independent datasources. The idea is to compute a list of data-facts that should be inserted to the amalgamated database or retracted from it in order to restore its consistency. This method is implemented by an abductive solver, called A system, that applies SLDNFA-resolution on a meta-theory that relates different, possibly contradicting, input databases. We also give a pure model-theoretic analysis of the possible ways to 'recover' consistent data from an inconsistent database in terms of those models of the database that exhibit as minimal inconsistent information as reasonably possible. This allows us to characterize the 'recovered databases' in terms of the 'preferred' (i.e., most consistent) models of the theory. The outcome is an abductive-based application that is sound and complete with respect to a corresponding model-based, preferential semantics, and - to the best of our knowledge - is more expressive (thus more general) than any other implementation of coherent integration of databases.

Connected through hyperedge HE-1 (induced by source paper "example driven query intent discovery abductive reasoning using semantic similarity"):
  with members:
    - "learning from positive and unlabeled data a survey"
    - "the complexity of reverse engineering problems for conjunctive queries"
    - "causes for query answers from databases datalog abduction view updates and integrity constraints"
    - "compositional vector space models for knowledge base completion"
    - "querying knowledge graphs by example entity tuples"
    - "learning and verifying quantified boolean queries by example"

Connected through hyperedge HE-2 (induced by source paper "causes for query answers from databases datalog abduction view updates and integrity constraints"):
  with members:
    - "quantifying causal effects on query answering in databases"
    - "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"
    - "responsibility and blame a structural model approach"

Connected through hyperedge HE-3 (induced by source paper "causes for query answers from databases datalog abduction and view updates the presence of integrity constraints"):
  with members:
    - "query answer causality in databases abductive diagnosis and view updates"
    - "from causes for database queries to repairs and model based diagnosis and back"
    - "the complexity of causality and responsibility for query answers and non answers"

Connected through hyperedge HE-4 (induced by source paper "from causes for database queries to repairs and model based diagnosis and back"):
  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"
    - "unifying causality diagnosis repairs and view updates in databases"
    - "causality in databases the diagnosis and repair connections"
    - "achieving data privacy through secrecy views and null based virtual updates"
    - "the complexity of causality and responsibility for query answers and non answers"
    - "approximate model based diagnosis using greedy stochastic search"
    - "prioritized repairing and consistent query answering in relational databases"

Connected through hyperedge HE-5 (induced by source paper "dynamics of belief abduction horn knowledge base and database updates"):
  with members:
    - "comparative study of view update algorithms in rational choice theory"
    - "on the complexity of second best abductive explanations"
    - "a new rational algorithm for view updating in relational databases"
    - "an abductive framework for horn knowledge base dynamics"
    - "a rational and efficient algorithm for view revision in databases"
    - "each normal logic program has a 2 valued minimal hypotheses semantics"
    - "admissible and restrained revision"
    - "new polynomial classes for logic based abduction"

Connected through hyperedge HE-6 (induced by source paper "query answer causality in databases abductive diagnosis and view updates"):
  with members:
    - "from causes for database queries to repairs and model based diagnosis and back"
    - "a modification of the halpern pearl definition of causality"
    - "unifying causality diagnosis repairs and view updates in databases"
    - "causality in databases the diagnosis and repair connections"
    - "achieving data privacy through secrecy views and null based virtual updates"
    - "the complexity of causality and responsibility for query answers and non answers"
    - "responsibility and blame a structural model approach"

Connected through hyperedge HE-7 (induced by source paper "an abductive framework for horn knowledge base dynamics"):
  with members:
    - "comparative study of view update algorithms in rational choice theory"
    - "on the complexity of second best abductive explanations"
    - "a new rational algorithm for view updating in relational databases"
    - "the view update problem for indefinite databases"
    - "each normal logic program has a 2 valued minimal hypotheses semantics"
    - "compilability of propositional abduction"
    - "an abductive framework for computing knowledge base updates"
    - "new polynomial classes for logic based abduction"

Connected through hyperedge HE-8 (induced by source paper "unifying causality diagnosis repairs and view updates in databases"):
  with members:
    - "causality in databases the diagnosis and repair connections"
    - "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"
    - "complexity of consistent query answering in databases under cardinality based and incremental repair semantics"
    - "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.AI(Artificial Intelligence)