human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "Applying ILP to Diterpene Structure Elucidation from 13 C NMR Spectra"):
  Abstract: We present a novel application of ILP to the problem of diterpene structure elucidation from 13 C NMR spectra. Diterpenes are organic compounds of low molecular weight that are based on a skeleton of 20 carbon atoms. They are of significant chemical and commercial interest because of their use as lead compounds in the search for new pharmaceutical effectors. The structure elucidation of diterpenes based on 13 C NMR spectra is usually done manually by human experts with specialized background knowledge on peak patterns and chemical structures. In the process, each of the 20 skeletal atoms is assigned an atom number that corresponds to its proper place in the skeleton and the diterpene is classified into one of the possible skeleton types. We address the problem of learning classification rules from a database of peak patterns for diterpenes with known structure. Recently, propositional learning was successfully applied to learn classification rules from spectra with assigned atom numbers. As the assignment of atom numbers is a difficult process in itself (and possibly indistinguishable from the classification process), we apply ILP, i.e., relational learning, to the problem of classifying spectra without assigned atom numbers.

Includes members:
  Member "Rule Induction with CN2: Some Recent Improvements":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Multi-class problems and discretization in ICL Extended abstract")
  Member "An intelligent search method using Inductive Logic Programming":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Combining FOIL and EBG to Speed-up Logic Programs")
  Member "Inductive Constraint Logic":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Applications of a logical discovery engine")
  Member "Generating Declarative Language Bias for Top-Down ILP Algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "A Comparison of Pruning Methods for Relational Concept Learning")
  Member "Lookahead and Discretization in ILP":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Top-down Induction of Logical Decision Trees")

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) 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