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: "Subsymbolic Case-Role Analysis of Sentences with Embedded Clauses"
  Abstract: A distributed neural network model called SPEC for processing sentences with recursive relative clauses is described. The model is based on separating the tasks of segmenting the input word sequence into clauses, forming the case-role representations, and keeping track of the recursive embeddings into different modules. The system needs to be trained only with the basic sentence constructs, and it generalizes not only to new instances of familiar relative clause structures, but to novel structures as well. SPEC exhibits plausible memory degradation as the depth of the center embeddings increases, its memory is primed by earlier constituents, and its performance is aided by semantic constraints between the constituents. The ability to process structure is largely due to a central executive network that monitors and controls the execution of the entire system. This way, in contrast to earlier subsymbolic systems, parsing is modeled as a controlled high-level process rather than one based on automatic reflex responses.

Connected through hyperedge HE-1 (induced by source paper "Disambiguation and Grammar as Emergent Soft Constraints"):
  with members:
    - "Book Review  Introduction to the Theory of Neural Computation Reviewed by: 2"

Connected through hyperedge HE-2 (induced by source paper "Learning Feature-based Semantics with Simple Recurrent Networks"):
  with members:
    - "On the Applicability of Neural Network and Machine Learning Methodologies to Natural Language Processing"

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: Neural_Networks