Key term extraction using a sentence based weighted TF-IDF algorithm
Автор: T. Vetriselvi, N. P. Gopalan, G. Kumaresan
Журнал: International Journal of Education and Management Engineering @ijeme
Статья в выпуске: 4 vol.9, 2019 года.
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Keyword ranking with similarity identification is an approach to find the significant Keywords in a corpus using a Variant Term Frequency Inverse Document Frequency (VTF-IDF) algorithm. Some of these may have same similarity and they get reduced to a single term when WordNet is used. The proposed approach that does not require any test or training set, assigns sentence based Weightage to the keywords(terms) and it is found to be effective. Its suitability is analyzed with several data sets using precision and recall as metrics.
Similarity Matrix, Term Count, WordNet
Короткий адрес: https://sciup.org/15015809
IDR: 15015809 | DOI: 10.5815/ijeme.2019.04.02
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