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: "complexity of consistent query answering in databases under cardinality based and incremental repair semantics"
  Abstract: Consistent Query Answering (CQA) is the problem of computing from a database the answers to a query that are consistent with respect to certain integrity constraints that the database, as a whole, may fail to satisfy. Consistent answers have been characterized as those that are invariant under certain minimal forms of restoration of the database consistency. We investigate algorithmic and complexity theoretic issues of CQA under database repairs that minimally depart -wrt the cardinality of the symmetric difference- from the original database. We obtain first tight complexity bounds. #R##N#We also address the problem of incremental complexity of CQA, that naturally occurs when an originally consistent database becomes inconsistent after the execution of a sequence of update operations. Tight bounds on incremental complexity are provided for various semantics under denial constraints. Fixed parameter tractability is also investigated in this dynamic context, where the size of the update sequence becomes the relevant parameter.

Connected through hyperedge HE-1 (induced by source paper "querying and repairing inconsistent prioritized knowledge bases complexity analysis and links with abstract argumentation"):
  with members:
    - "the dl lite family and relations"
    - "prioritized repairing and consistent query answering in relational databases"

Connected through hyperedge HE-2 (induced by source paper "principles of progress indicators for database repairing"):
  with members:
    - "measuring and computing database inconsistency via repairs"
    - "research directions for principles of data management dagstuhl perspectives workshop 16151"
    - "holoclean holistic data repairs with probabilistic inference"
    - "computing optimal repairs for functional dependencies"
    - "matching dependencies with arbitrary attribute values semantics query answering and integrity constraints"

Connected through hyperedge HE-3 (induced by source paper "repair based degrees of database inconsistency computation and complexity"):
  with members:
    - "computing optimal repairs for functional dependencies"
    - "consistency and trust in peer data exchange systems"
    - "juggling functions inside a database"
    - "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"
    - "minimal change integrity maintenance using tuple deletions"

Connected through hyperedge HE-4 (induced by source paper "a formal framework for probabilistic unclean databases"):
  with members:
    - "the complexity of computing a cardinality repair for functional dependencies"
    - "holoclean holistic data repairs with probabilistic inference"
    - "computing optimal repairs for functional dependencies"
    - "implicit regularization in nonconvex statistical estimation gradient descent converges linearly for phase retrieval matrix completion and blind deconvolution"
    - "minimal change integrity maintenance using tuple deletions"

Connected through hyperedge HE-5 (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"
    - "quantifying causal effects on query answering in databases"
    - "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"
    - "minimal change integrity maintenance using tuple deletions"

Connected through hyperedge HE-6 (induced by source paper "computing optimal repairs for functional dependencies"):
  with members:
    - "principles of progress indicators for database repairing"
    - "repair based degrees of database inconsistency computation and complexity"
    - "measuring and computing database inconsistency via repairs"
    - "holoclean holistic data repairs with probabilistic inference"
    - "prioritized repairing and consistent query answering in relational databases"
    - "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:
    - "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"
    - "coherent integration of databases by abductive logic programming"
    - "responsibility and blame a structural model approach"

Connected through hyperedge HE-8 (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"

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)