An Algorithm for Text Categorization

Abstract

A novel and efficient learning algorithm is proposed for the binary linear classification problem. The algorithm is trained using the Rocchio’s relevance feedback technique and builds a classifier by the intermediate hyperplane of two common tangent hyperplanes for the given category and its complement. Experimental results presented are very encouraging and justify the need for further research.

Publication
In The 31st Annual International ACM SIGIR Conference, 20-24 July 2008, Singapore
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