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: "Efficient subgraph matching on billion node graphs"
  Abstract: The ability to handle large scale graph data is crucial to an increasing number of applications. Much work has been dedicated to supporting basic graph operations such as subgraph matching, reachability, regular expression matching, etc. In many cases, graph indices are employed to speed up query processing. Typically, most indices require either super-linear indexing time or super-linear indexing space. Unfortunately, for very large graphs, super-linear approaches are almost always infeasible. In this paper, we study the problem of subgraph matching on billion-node graphs. We present a novel algorithm that supports efficient subgraph matching for graphs deployed on a distributed memory store. Instead of relying on super-linear indices, we use efficient graph exploration and massive parallel computing for query processing. Our experimental results demonstrate the feasibility of performing subgraph matching on web-scale graph data.

Connected through hyperedge HE-1 (induced by source paper "Holistic Subgraph Search over Large Graphs"):
  with members:
    (none)

Connected through hyperedge HE-2 (induced by source paper "Fast Graph Pattern Matching"):
  with members:
    - "Query optimization"
    - "PEGASUS: A Peta-Scale Graph Mining System Implementation and Observations"
    - "A flexible graph pattern matching framework via indexing"

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