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: "Aligning Textual and Graphical Descriptions of Processes Through ILP Techniques"
  Abstract: With the aim of having individuals from different backgrounds and expertise levels examine the operations in an organization, different representations of business processes are maintained. To have these different representations aligned is not only a desired feature, but also a real challenge due to the contrasting nature of each process representation. In this paper we present an efficient technique for aligning a textual description and a graphical model of a process. The technique is grounded on using natural language processing techniques to extract linguistic features of each representation, and encode the search as a mathematical optimization encoded using Integer Linear Programming (ILP) whose resolution ensures an optimal alignment between both descriptions. The technique has been implemented and the experiments witness the significance of the approach with respect to the state-of-the-art technique for the same task.

Connected through hyperedge HE-1 (induced by source paper "Aligning textual and model-based process descriptions"):
  with members:
    (none)

Connected through hyperedge HE-2 (induced by source paper "The Stanford CoreNLP Natural Language Processing Toolkit"):
  with members:
    - "Information extraction from multi-institutional radiology reports"
    - "Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank"
    - "The price of debiasing automatic metrics in natural language evalaution."
    - "HANS: A Service-Oriented Framework for Chinese Language Processing"

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