An algorithm for text categorization

Authors:
Anestis Gkanogiannis;Theodore Kalamboukis
Affiliations:
Athens University of Economics and Business, Athens, Greece;Athens University of Economics and Business, Athens, Greece
Venue:
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Year:
2008

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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.