Question Classification with Incremental Rule Learning Algorithm Based on Rough Set
一种基于粗糙集增量式规则学习的问题分类方法研究

This paper presents a method on automatic question classification through incremental rule learning based on rough set theory. The core of the method is appling the machine learning approach to gain classified rules automatically through extract the features of query sentence thoroughly, and the decision table is used to construct the training collection. Comparing with the alternative means, the superiority is that it acquires the classified rule automatically and uses the rough set method to obtain the optimized smallest rule set. Especially, the incremental learning is induced to improve the precision and avoid the tedious re-training process. The performance of the approach is promising, when tested on opposite test. Meanwhile, the method obtains a very good result in the international TREC2005 Q/A track.