Journal of Intelligence and Information Systems (지능정보연구)

Korea Intelligent Information System Society (한국지능정보시스템학회)
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Second-Order Learning for Complex Forecasting Tasks: Case Study of Video-On-Demand

복잡한 예측문제에 대한 이차학습방법 : Video-On-Demand에 대한 사례연구

  • Published : 1997.06.01
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Abstract

To date, research on data mining has focused primarily on individual techniques to su, pp.rt knowledge discovery. However, the integration of elementary learning techniques offers a promising strategy for challenging a, pp.ications such as forecasting nonlinear processes. This paper explores the utility of an integrated a, pp.oach which utilizes a second-order learning process. The a, pp.oach is compared against individual techniques relating to a neural network, case based reasoning, and induction. In the interest of concreteness, the concepts are presented through a case study involving the prediction of network traffic for video-on-demand.

Keywords

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