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: "using description logics for rdf constraint checking and closed world recognition"
  Abstract: RDF and Description Logics work in an open-world setting where absence of information is not information about absence. Nevertheless, Description Logic axioms can be interpreted in a closed-world setting and in this setting they can be used for both constraint checking and closed-world recognition against information sources. When the information sources are expressed in well-behaved RDF or RDFS (i.e., RDF graphs interpreted in the RDF or RDFS semantics) this constraint checking and closed-world recognition is simple to describe. Further this constraint checking can be implemented as SPARQL querying and thus effectively performed.

Connected through hyperedge HE-1 (induced by source paper "linked open data validity a technical report from isws 2018"):
  with members:
    - "tell me why is it so explaining knowledge graph relationships by finding descriptive support passages"
    - "a comprehensive survey of graph embedding problems techniques and applications"
    - "node2vec scalable feature learning for networks"
    - "word tagging with foundational ontology classes extending the wordnet dolce mapping to verbs"
    - "application of ontologies in identifying requirements patterns in use cases"
    - "efficient estimation of word representations in vector space"

Connected through hyperedge HE-2 (induced by source paper "completeness and consistency analysis for evolving knowledge bases"):
  with members:
    - "quality assessment of linked datasets using probabilistic approximation"
    - "smote synthetic minority over sampling technique"

Connected through hyperedge HE-3 (induced by source paper "validating and describing linked data portals using shapes"):
  with members:
    - "shape expressions schemas"
    - "semantics and complexity of sparql"

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)