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: "Reasoning with Portions of Precedents"
  Abstract: This paper argues that the task of matching in case-based reasoning can often be improved by comparing new cases to portions of precedents. An example is presented that illustrates how combining portions of multiple precedents can permit new cases to be resolved that would be indeterminate if new cases could only be compared to entire precedents. A system that uses of portions of precedents for legal analysis in the domain of Texas worker's compensation law, GREBE, is described, and examples of GREBE's analysis that combine reasoning steps from multiple precedents are presented.

Connected through hyperedge HE-1 (induced by source paper "Four Challenges for a Computational Model of Legal Precedent"):
  with members:
    (none)

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