File system wide file classification with agents
Benjamin Martin · 2003
Many semi structured information systems such as file systems and email clients allow data to be tagged as belonging in many categories. Some such systems support notions similar to emblems, where files can be semantically tagged as fitting into a broad category by associating a file with an emblem. This paper presents a file system that makes use of Supervised machine learning for the creation of agents to offer fuzzy assertions and retractions of semantic tags on a per file basis. Such assertions are then subject to a belief resolution system to obtain an overall picture for a file’s emblem attachments.