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 and approximation of fixing numerical attributes in databases under integrity constraints"
  Abstract: Consistent query answering is the problem of computing the answers from a database that are consistent with respect to certain integrity constraints that the database as a whole may fail to satisfy. Those answers are characterized as those that are invariant under minimal forms of restoring the consistency of the database. In this context, we study the problem of repairing databases by fixing integer numerical values at the attribute level with respect to denial and aggregation constraints. We introduce a quantitative definition of database fix, and investigate the complexity of several decision and optimization problems, including DFP, i.e. the existence of fixes within a given distance from the original instance, and CQA, i.e. deciding consistency of answers to aggregate conjunctive queries under different semantics. We provide sharp complexity bounds, identify relevant tractable cases; and introduce approximation algorithms for some of those that are intractable. More specifically, we obtain results like undecidability of existence of fixes for aggregation constraints; MAXSNP-hardness of DFP, but a good approximation algorithm for a relevant special case; and intractability but good approximation for CQA for aggregate queries for one database atom denials (plus built-ins).

Connected through hyperedge HE-1 (induced by source paper "a hybrid data cleaning framework using markov logic networks"):
  with members:
    - "holoclean holistic data repairs with probabilistic inference"
    - "on the relative trust between inconsistent data and inaccurate constraints"
    - "tuffy scaling up statistical inference in markov logic networks using an rdbms"

Connected through hyperedge HE-2 (induced by source paper "consistent query answers in the presence of universal constraints"):
  with members:
    - "complexity of consistent query answering in databases under cardinality based and incremental repair semantics"
    - "preferred answer sets for ordered logic programs"
    - "answer sets for consistent query answering in inconsistent databases"
    - "minimal change integrity maintenance using tuple deletions"
    - "dlv a system for declarative problem solving"

Connected through hyperedge HE-3 (induced by source paper "world set decompositions expressiveness and efficient algorithms"):
  with members:
    - "10 10 6 worlds and beyond efficient representation and processing of incomplete information"
    - "answer sets for consistent query answering in inconsistent databases"

Connected through hyperedge HE-4 (induced by source paper "complexity of consistent query answering in databases under cardinality based and incremental repair semantics"):
  with members:
    - "the dlv system for knowledge representation and reasoning"
    - "consistent query answers on numerical databases under aggregate constraints"
    - "answer sets for consistent query answering in inconsistent databases"
    - "minimal change integrity maintenance using tuple deletions"

Connected through hyperedge HE-5 (induced by source paper "consistent query answers on numerical databases under aggregate constraints"):
  with members:
    - "answer sets for consistent query answering in inconsistent databases"
    - "minimal change integrity maintenance using tuple deletions"

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)