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 "Structural Similarity and Adaptation"):
  Abstract: Most commonly, case-based reasoning is applied in domains where attribute value representations of cases are sufficient to represent the features relevant to support classification, diagnosis or design tasks. Distance functions like the Hamming-distance or their transformation into similarity functions are applied to retrieve past cases to be used to generate the solution of an actual problem. Often, domain knowledge is available to adapt past solutions to new problems or to evaluate solutions. However, there are domains like architectural design or law in which structural case representations and corresponding structural similarity functions are needed. Often, the acquisition of adaptation knowledge seems to be impossible or rather requires an effort that is not manageable for fielded applications. Despite of this, humans use cases as the main source to generate adapted solutions. How to achieve this computationally? This paper presents a general approach to structural similarity assessment and adaptation. The approach allows to explore structural case representations and limited domain knowledge to support design tasks. It is exemplarily instantiated in three modules of the design assistant FABEL-Idea that generates adapted design solutions on the basis of prior CAD layouts.

Includes members:
  Member "Structural Similarity as Guidance in Case-Based Design":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Conceptual Analogy")
  Member "Automatic Indexing, Retrieval and Reuse of Topologies in Architectual Layouts":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Structural Similarity as Guidance in Case-Based Design")
  Member "A Preprocessing Model for Integrating CBR and Prototype-Based Neural Networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Conceptual Analogy: Conceptual clustering for informed and efficient analogical reasoning")

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