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: "Structural Similarity as Guidance in Case-Based Design"
  Abstract: This paper presents a novel approach to determine structural similarity as guidance for adaptation in case-based reasoning (Cbr). We advance structural similarity assessment which provides not only a single numeric value but the most specific structure two cases have in common, inclusive of the modification rules needed to obtain this structure from the two cases. Our approach treats retrieval, matching and adaptation as a group of dependent processes. This guarantees the retrieval and matching of not only similar but adaptable cases. Both together enlarge the overall problem solving performance of Cbr and the explainability of case selection and adaptation considerably. Although our approach is more theoretical in nature and not restricted to a specific domain, we will give an example taken from the domain of industrial building design. Additionally, we will sketch two prototypical implementations of this approach.

Connected through hyperedge HE-1 (induced by source paper "Conceptual Analogy"):
  with members:
    - "(1994); Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. Case-Based Reasoning: Foundational Issues, Methodological"
    - "Towards Formalizations in Case-Based Reasoning for Synthesis"
    - "Task-Oriented Knowledge Acquisition and Reasoning for Design Support Systems"

Connected through hyperedge HE-2 (induced by source paper "Conceptual Analogy: Conceptual clustering for informed and efficient analogical reasoning"):
  with members:
    - "A Preprocessing Model for Integrating CBR and Prototype-Based Neural Networks"

Connected through hyperedge HE-3 (induced by source paper "S o l u t i o n Relevant A b s t r a"):
  with members:
    - "Supporting Combined Human and Machine Planning: An Interface for Planning by Analogical Reasoning"

Connected through hyperedge HE-4 (induced by source paper "Structural Similarity and Adaptation"):
  with members:
    - "Automatic Indexing, Retrieval and Reuse of Topologies in Architectual Layouts"
    - "A Preprocessing Model for Integrating CBR and Prototype-Based Neural Networks"

Connected through hyperedge HE-5 (induced by source paper "MAC/FAC: A Model of Similarity-based Retrieval"):
  with members:
    - "Task-Oriented Knowledge Acquisition and Reasoning for Design Support Systems"
    - "The Structure-Mapping Engine: Algorithm and Examples"
    - "Context-Based Similarity Applied to Retrieval of Relevant Cases"
    - "In  Estimating analogical similarity by dot-products of Holographic Reduced Representations."
    - "Proceedings of CogSci89 Structural Evaluation of Analogies: What Counts?"
    - "Making SME greedy and pragmatic"

Connected through hyperedge HE-6 (induced by source paper "Task-Oriented Knowledge Acquisition and Reasoning for Design Support Systems"):
  with members:
    - "Conceptual Analogy"
    - "Towards Formalizations in Case-Based Reasoning for Synthesis"
    - "MAC/FAC: A Model of Similarity-based Retrieval"

Connected through hyperedge HE-7 (induced by source paper "Towards Formalizations in Case-Based Reasoning for Synthesis"):
  with members:
    - "Conceptual Analogy"
    - "Task-Oriented Knowledge Acquisition and Reasoning for Design Support Systems"
    - "Structure oriented case retrieval"

Connected through hyperedge HE-8 (induced by source paper "Automatic Indexing, Retrieval and Reuse of Topologies in Architectual Layouts"):
  with members:
    - "Structural Similarity and Adaptation"
    - "Fish and Shrink. A next step towards e-cient case retrieval in large scaled case bases"

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: Case_Based