http://researchonline.federation.edu.au/vital/access/manager/Index en-us 5 http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:9301 Wed 07 Apr 2021 13:54:30 AEST ]]> http://researchonline.federation.edu.au/vital/access/manager/Repository/vital:3836 2 statistic, and Odds Ratio. From the literature there are three term ranking methods to summarize term weights of different categories for multi-class text categorization. They are Summation, Average, and Maximum methods. In this paper we present a new term ranking method to summarize term weights, i.e. Maximum Gap. Using two different methods of information gain and χ² statistic, we setup controlled experiments for different term ranking methods. Reuter-21578 text corpus is used as the dataset. Two popular classification algorithms SVM and Boostexter are adopted to evaluate the performance of different term ranking methods. Experimental results show that the new term ranking method performs better. © 2010 Springer-Verlag.]]> Wed 07 Apr 2021 13:34:53 AEST ]]>