@article{MAKHILLAJIT2005434906,
    title = {An Effective Approach to the Evaluation and Construction of Training Corpus for Text Classification},
    journal = {Asian Journal of Information Technology},
    volume = {4},
    number = {3},
    pages = {33-40},
    year = {2005},
    issn = {1682-3915},
    doi = {ajit.2005.33.40},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2005.33.40},
    author = {Jihong Guan and},
    keywords = {},
    abstract = {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.}
    }