human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent groups of papers sharing a common citing paper.

Details of the hypergraph:
Center node: "Inductive Database Design"
  Abstract: When designing a (deductive) database, the designer has to decide for each predicate (or relation) whether it should be defined extensionally or intensionally, and what the definition should look like. An intelligent system is presented to assist the designer in this task. It starts from an example database in which all predicates are defined extensionally. It then tries to compact the database by transforming extensionally defined predicates into intensionally defined ones. The intelligent system employs techniques from the area of inductive logic programming.

Connected through hyperedge HE-1 (induced by source paper "Applications of a logical discovery engine"):
  with members:
    - "Application of Clausal Discovery to Temporal Databases"
    - "Inductive Constraint Logic"
    - "Inductive Constraint Logic and the Mutagenesis Problem"

Connected through hyperedge HE-2 (induced by source paper "Learning with Abduction"):
  with members:
    - "Inductive Constraint Logic"
    - "The ILP description learning problem: Towards a general model-level definition of data mining in ILP"

Connected through hyperedge HE-3 (induced by source paper "Dlab: A Declarative Language Bias Formalism"):
  with members:
    - "Evaluation and Selection of Biases in Machine Learning"

Question: Please tell me which class the center node belongs to. The 7 classes are: Neural_Networks, Reinforcement_Learning, Probabilistic_Methods, Theory, Genetic_Algorithms, Case_Based, Rule_Learning. Directly output the class name.

gpt: Rule_Learning