TY  - JOUR
T1  - An Effective Approach to the Evaluation and Construction of Training Corpus for Text Classification
AU - , Jihong Guan AU - , Shuigeng Zhou 
JO  - Asian Journal of Information Technology
VL  - 4
IS  - 3
SP  - 33
EP  - 40
PY  - 2005
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2005.33.40
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2005.33.40
KW  - 
AB  - Text classification is becoming more and more important with the rapid growth of on-line information available. It was observed that the quality of training corpus impacts the performance of the trained classifier. This paper proposes an approach to build high-quality training corpuses for better classification performance by first exploring the properties of training corpuses, and then giving an algorithm for constructing training corpuses semi-automatically. Preliminary experimental results validate our approach: classifiers based on the training corpuses constructed by our approach can achieve good performance while the training corpus` size is significantly reduced. Our approach can be used for building efficient and lightweight classification systems.
ER  -