A novel method and a framework called Memory-Based Forecasting are proposed to forecast complex and timevarying natural patterns with the goal of supporting experts' decision...
It is challenging to support the timeliness of realtime data service requests in data-intensive real-time applications such as online auction or stock trading, while maintaining t...
Mining frequent patterns in databases is a fundamental and essential problem in data mining research. A continuity is a kind of causal relationship which describes a definite temp...
Abstract This paper presents an approach to designing and implementing extensible computational models for perceiving systems based on a knowledge-driven joint inference approach. ...
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...