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: "Fast Graph Pattern Matching"
  Abstract: Due to rapid growth of the Internet technology and new scientific/technological advances, the number of applications that model data as graphs increases, because graphs have high expressive power to model complicated structures. The dominance of graphs in real-world applications asks for new graph data management so that users can access graph data effectively and efficiently. In this paper, we study a graph pattern matching problem over a large data graph. The problem is to find all patterns in a large data graph that match a user-given graph pattern. We propose a new two-step R-join (reachability join) algorithm with filter step and fetch step based on a cluster- based join-index with graph codes. We consider the filter step as an R-semijoin, and propose a new optimization approach by interleaving R-joins with R-semijoins. We conducted extensive performance studies, and confirm the efficiency of our proposed new approaches.

Connected through hyperedge HE-1 (induced by source paper "PEGASUS: A Peta-Scale Graph Mining System Implementation and Observations"):
  with members:
    - "Managing large dynamic graphs efficiently"

Connected through hyperedge HE-2 (induced by source paper "Query optimization"):
  with members:
    - "Federated database systems for managing distributed, heterogeneous, and autonomous databases"

Connected through hyperedge HE-3 (induced by source paper "A flexible graph pattern matching framework via indexing"):
  with members:
    (none)

Connected through hyperedge HE-4 (induced by source paper "Efficient subgraph matching on billion node graphs"):
  with members:
    - "Holistic Subgraph Search over Large Graphs"

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