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 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.

Connected through hyperedge HE-1 (induced by source paper "Structural Similarity as Guidance in Case-Based Design"):
  with members:
    - "Conceptual Analogy"
    - "Towards Formalizations in Case-Based Reasoning for Synthesis"
    - "Task-Oriented Knowledge Acquisition and Reasoning for Design Support Systems"
    - "MAC/FAC: A Model of Similarity-based Retrieval"
    - "Conceptual Analogy: Conceptual clustering for informed and efficient analogical reasoning"
    - "S o l u t i o n Relevant A b s t r a"
    - "Automatic Indexing, Retrieval and Reuse of Topologies in Architectual Layouts"

Connected through hyperedge HE-2 (induced by source paper "Automatic Indexing, Retrieval and Reuse of Topologies in Architectual Layouts"):
  with members:
    - "Structural Similarity as Guidance in Case-Based Design"
    - "Fish and Shrink. A next step towards e-cient case retrieval in large scaled case bases"

Connected through hyperedge HE-3 (induced by source paper "A Preprocessing Model for Integrating CBR and Prototype-Based Neural Networks"):
  with members:
    - "Conceptual Analogy: Conceptual clustering for informed and efficient analogical reasoning"

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