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: "Extending Complex Event Processing to Graph-structured Information"
  Abstract: Complex Event Processing (CEP) is a powerful technology in realtime distributed environments for analyzing fast and distributed streams of data, and deriving conclusions from them. CEP permits defining complex events based on the events produced by the incoming sources in order to identify complex meaningful circumstances and to respond to them as quickly as possible. However, in many situations the information that needs to be analyzed is not structured as a mere sequence of events, but as graphs of interconnected data that evolve over time. This paper proposes an extension of CEP systems that permits dealing with graph-structured information. Two case studies are used to validate the proposal and to compare its performance with traditional CEP systems. We discuss the benefits and limitations of the CEP extensions presented.

Connected through hyperedge HE-1 (induced by source paper "Mogwaï: A framework to handle complex queries on large models"):
  with members:
    - "Performance of graph query languages: comparison of cypher, gremlin and native access in Neo4j"

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