Associative Classification has been successfully employed in many diverse classification problem domains, showing high classification accuracy and adequate computation time relative to the other traditionally used solutions. Despite this, very little research has been conducted with it in the problem area of Text Categorisation and only a small number of approaches presently exist that are based on the concept. This paper aims to highlight the main characteristics of general Text Categorisation problems, provide an overview of the principal drawbacks associated with traditionally employed techniques and outline the benefits of utilising Associative Classification methods as a replacement. The potential disadvantages of the approach are also considered and a range of examples is included for each section in order to present a balanced representation that is unbiased
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