Abstract
The term weighting scheme, which is used to convert the documents to vectors in the term space, is a vital step in automatic text categorization. The previous studies showed that term weighting schemes dominate the performance. There have been extensive studies on term weighting for English text classification. However, not many works have been studied on Vietnamese text classification.. In this paper, we proposed a term weighting scheme called normalizetf.rfmax, which is based on tf.rf term weighting scheme --- one of the most effective term weighting schemes to date. We conducted experiments to compare our proposed normalizetf.rfmax term weighting scheme to tf.rf and tf.idf on Vietnamese text classification benchmark. The results showed that our proposed term weighting scheme can achieve about 3i¾?%---5i¾?% accuracy better than other term weighting schemes.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.