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: "A unified framework for monitoring data streams in real time"
  Abstract: Online monitoring of data streams poses a challenge in many data-centric applications, such as telecommunications networks, traffic management, trend-related analysis, Web-click streams, intrusion detection, and sensor networks. Mining techniques employed in these applications have to be efficient in terms of space usage and per-item processing time while providing a high quality of answers to (1) aggregate monitoring queries, such as finding surprising levels of a data stream, detecting bursts, and to (2) similarity queries, such as detecting correlations and finding interesting patterns. The most important aspect of these tasks is their need for flexible query lengths, i.e., it is difficult to set the appropriate lengths a priori. For example, bursts of events can occur at variable temporal modalities from hours to days to weeks. Correlated trends can occur at various temporal scales. The system has to discover "interesting" behavior online and monitor over flexible window sizes. In this paper, we propose a multi-resolution indexing scheme, which handles variable length queries efficiently. We demonstrate the effectiveness of our framework over existing techniques through an extensive set of experiments.

Connected through hyperedge HE-1 (induced by source paper "Efficient Similarity Search over Future Stream Time Series"):
  with members:
    - "A review on time series data mining"

Connected through hyperedge HE-2 (induced by source paper "Classification Using Streaming Random Forests"):
  with members:
    - "Incremental Learning of Concept Drift from Streaming Imbalanced Data"

Connected through hyperedge HE-3 (induced by source paper "Resource sharing in continuous sliding-window aggregates"):
  with members:
    - "Approximate counts and quantiles over sliding windows"

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