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: "data cleaning and query answering with matching dependencies and matching functions"
  Abstract: Matching dependencies were recently introduced as declarative rules for data cleaning and entity resolution. Enforcing a matching dependency on a database instance identifies the values of some attributes for two tuples, provided that the values of some other attributes are sufficiently similar. Assuming the existence of matching functions for making two attributes values equal, we formally introduce the process of cleaning an instance using matching dependencies, as a chase-like procedure. We show that matching functions naturally introduce a lattice structure on attribute domains, and a partial order of semantic domination between instances. Using the latter, we define the semantics of clean query answering in terms of certain/possible answers as the greatest lower bound/least upper bound of all possible answers obtained from the clean instances. We show that clean query answering is intractable in some cases. Then we study queries that behave monotonically wrt semantic domination order, and show that we can provide an under/over approximation for clean answers to monotone queries. Moreover, non-monotone positive queries can be relaxed into monotone queries.

Connected through hyperedge HE-1 (induced by source paper "holoclean holistic data repairs with probabilistic inference"):
  with members:
    - "rapidly mixing gibbs sampling for a class of factor graphs using hierarchy width"
    - "truth finding on the deep web is the problem solved"
    - "slimfast guaranteed results for data fusion and source reliability"
    - "incremental knowledge base construction using deepdive"
    - "hinge loss markov random fields and probabilistic soft logic"
    - "dimmwitted a study of main memory statistical analytics"
    - "uniform solution sampling using a constraint solver as an oracle"
    - "on the relative trust between inconsistent data and inaccurate constraints"

Connected through hyperedge HE-2 (induced by source paper "efficient discovery of ontology functional dependencies"):
  with members:
    - "effective and complete discovery of order dependencies via set based axiomatization"
    - "discovering matching dependencies"

Connected through hyperedge HE-3 (induced by source paper "enforcing relational matching dependencies with datalog for entity resolution"):
  with members:
    - "erblox combining matching dependencies with machine learning for entity resolution"
    - "the dlv system for knowledge representation and reasoning"

Connected through hyperedge HE-4 (induced by source paper "erblox combining matching dependencies with machine learning for entity resolution"):
  with members:
    - "enforcing relational matching dependencies with datalog for entity resolution"
    - "a comparison of blocking methods for record linkage"
    - "large scale collective entity matching"
    - "discovering matching dependencies"

Connected through hyperedge HE-5 (induced by source paper "bayeswipe a scalable probabilistic framework for cleaning bigdata"):
  with members:
    - "crowder crowdsourcing entity resolution"
    - "on the relative trust between inconsistent data and inaccurate constraints"

Connected through hyperedge HE-6 (induced by source paper "tractable vs intractable cases of matching dependencies for query answering under entity resolution"):
  with members:
    - "charting the tractability frontier of certain conjunctive query answering"
    - "a dichotomy on the complexity of consistent query answering for atoms with simple keys"

Connected through hyperedge HE-7 (induced by source paper "query answering under matching dependencies for data cleaning complexity and algorithms"):
  with members:
    - "matching dependencies with arbitrary attribute values semantics query answering and integrity constraints"
    - "complexity of consistent query answering in databases under cardinality based and incremental repair semantics"
    - "answer sets for consistent query answering in inconsistent databases"
    - "minimal change integrity maintenance using tuple deletions"

Connected through hyperedge HE-8 (induced by source paper "matching dependencies with arbitrary attribute values semantics query answering and integrity constraints"):
  with members:
    - "complexity of consistent query answering in databases under cardinality based and incremental repair semantics"
    - "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"

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)