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: "Using Universal Linguistic Knowledge to Guide Grammar Induction"
  Abstract: We present an approach to grammar induction that utilizes syntactic universals to improve dependency parsing across a range of languages. Our method uses a single set of manually-specified language-independent rules that identify syntactic dependencies between pairs of syntactic categories that commonly occur across languages. During inference of the probabilistic model, we use posterior expectation constraints to require that a minimum proportion of the dependencies we infer be instances of these rules. We also automatically refine the syntactic categories given in our coarsely tagged input. Across six languages our approach outperforms state-of-the-art unsupervised methods by a significant margin.

Connected through hyperedge HE-1 (induced by source paper "Unsupervised Dependency Parsing with Transferring Distribution via Parallel Guidance and Entropy Regularization"):
  with members:
    - "The CoNLL 2007 Shared Task on Dependency Parsing"
    - "End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF"

Connected through hyperedge HE-2 (induced by source paper "Opinion Mining and Sentiment Analysis"):
  with members:
    - "Opinion Mining and Information Fusion"
    - "Sentiment analysis in Facebook and its application to e-learning"
    - "Utility scoring of product reviews"
    - "Opinion observer: analyzing and comparing opinions on the Web"
    - "Mining newsgroups using networks arising from social behavior"
    - "User-level sentiment analysis incorporating social networks"
    - "Emotions and Information Diffusion in Social Media—Sentiment of Microblogs and Sharing Behavior"
    - "Active Learning for Imbalanced Sentiment Classification"

Connected through hyperedge HE-3 (induced by source paper "Using semantic cues to learn syntax"):
  with members:
    - "Reducing the Size of the Representation for the uDOP-Estimate"

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