Instance-Based Prototypical Learning of Set Valued Attributes
نویسنده
چکیده
The aim of this project is to investigate and develop new machine learning techniques which can be applied to agent based applications such as those that assist in information filtering. The motivation for this work emerged from reviewing the literature on Interface Agents, and applying existing machine learning techniques to an intelligent interface agent which filtered incoming electronic mail. The results of this study highlighted the limitations of current learning algorithms when employed within information filtering agents, and provided the motivation to explore a new family of instance-based learning techniques.
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