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: "Essential Attributes Generation for Some Data Mining Tasks"
  Abstract: In this paper, we introduce a new approach referred to as Essential Attributes Generation (EAG) to reduce the dimensionality of multidimensional real-valued data series. We form a new representation of the original data. The approach is based on the concept of essential attributes generated by a multilayer neural network. The EAG generates a vector of real valued new attributes which form the compressed representation of the original data. The attributes are synthetic, and while not being directly interpretable, they still retain important features of the original data series. The approach has found applications to classification as well as clustering tasks.

Connected through hyperedge HE-1 (induced by source paper "A review on time series data mining"):
  with members:
    - "Efficient Similarity Search over Future Stream Time Series"
    - "Piecewise statistic approximation based similarity measure for time series"
    - "A multi-wavelet optimization approach using similarity measures for electrocardiogram signal classification"

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