human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "Integration of semantic and syntactic constraints for structural noun phrase disambiguation"
  Abstract: A fundamental problem in Natural Language Processing is the integration of syntactic and semantic constraints. In this paper we describe a new approach for the integration of syntactic and semantic constraints which takes advantage of a learned memory model. Our model combines localist representations for the integration of constraints and distributed representations for learning semantic constraints. We apply this model to the problem of structural disambiguation of noun phrases and show that a learned connectionist model can scale up the underlying memory of a Natural Language Processing system.

Connected through hyperedge HE-1 (induced by source paper "Massively Parallel Parsing: A Strongly Interactive Model of Natural Language Interpretation*"):
  with members:
    - "Introduction to the special issue on word sense disambiguation: the state of the art"
    - "Passing Markers: A Theory of Contextual Influence in Language Comprehension*"

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Computer science