Activity modelling using email and web page classification
author: Aaron Quigley,
University of Sydney
published: Feb. 25, 2007, recorded: July 2005, views: 3561
published: Feb. 25, 2007, recorded: July 2005, views: 3561
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Description
This work explores the modelling of a user’s current activity using a single document and a very small collection of classified documents. We describe the WeMAC approach for combining evidence from heterogeneous sources to give a prdict the user’s activity. We report evaluation of the WeMAC model using two different document types: emails and web pages; assess its performance on both tiny document sets and larger sets; and assess its performance against a “one bag” approach. We report promising results, with average F1 value of 0.5-0.7.
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