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 "Case Retrieval Nets: Basic Ideas and Extensions"):
  Abstract: An efficient retrieval of a relatively small number of relevant cases from a huge case base is a crucial subtask of Case-Based Reasoning. In this article, we present Case Retrieval Nets (CRNs), a memory model that has recently been developed for this task. The main idea is to apply a spreading activation process to a net-like case memory in order to retrieve cases being similar to a posed query case. We summarize the basic ideas of CRNs, suggest some useful extensions, and present some initial experimental results which suggest that CRNs can successfully handle case bases larger than considered usually in the CBR community.

Includes members:
  Member "Preparing Case Retrieval Nets for Distributed Processing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "(1994); Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. Case-Based Reasoning: Foundational Issues, Methodological")
  Member "Utilizing Connectionist Learning Procedures in Symbolic Case Retrieval Nets":
    also connected through other hyperedges:
      (none)
  Member "Technical Diagnosis: Fallexperte-D of further knowledge sources (domain knowledge, common knowledge) is investigated in the":
    also connected through other hyperedges:
      (none)
  Member "CBR on Semi-structured Documents: The ExperienceBook and the FAllQ Project":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "CBR for Document Retrieval: The FAllQ Project")
  Member "Case Retrieval Nets Applied to Large Case Bases":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Applying Case Retrieval Nets to Diagnostic Tasks in Technical Domains")
  Member "CBR for Document Retrieval: The FAllQ Project":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Applying Case Retrieval Nets to Diagnostic Tasks in Technical Domains")
  Member "Applying Case Retrieval Nets to Diagnostic Tasks in Technical Domains":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "Preparing Case Retrieval Nets for Distributed Processing")
  Member "An Investigation of Marker-Passing Algorithms for Analogue Retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "Preparing Case Retrieval Nets for Distributed Processing")

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: Case_Based