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: "Web Appearance Disambiguation of Personal Names Based on Network Motif"
  Abstract: Searching for information about a particular person is a common activity on search engines. However, current search engines do not provide any special function for search a person. Previous research has solved the problem by using additional background knowledge, such as a friend list, to cluster the searched web pages. However, it is still difficult to retrieve and choose suitable background knowledge. In this paper, we propose a Web Appearance Disambiguation (WAD) system to solve the problem by only using the hyperlink structures between web pages. The key idea of the WAD system is to find out smaller node motifs as evidences of close relationship between pages for clustering searched web pages. Our experimental results show that, under no background knowledge, the performance of the WAD system achieves 70% for the F-measure.

Connected through hyperedge HE-1 (induced by source paper "Two supervised learning approaches for name disambiguation in author citations"):
  with members:
    - "Training a naive bayes classifier via the EM algorithm with a class distribution constraint"
    - "A Fuzzy Semisupervised Clustering Method: Application to the Classification of Scientific Publications"

Connected through hyperedge HE-2 (induced by source paper "Named entity disambiguation by leveraging wikipedia semantic knowledge"):
  with members:
    - "Robust Disambiguation of Named Entities in Text"
    - "Improved text annotation with Wikipedia entities"

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