Multidocument Arabic Text Summarization Based on Clustering and Word2Vec to Reduce Redundancy
Arabic is one of the most semantically and syntactically complex languages in the world. A key challenging issue in text mining is text summarization, so we propose an unsupervised score-based method which combines the vector space model, continuous bag of words (CBOW), clustering, and a statistical...
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| Главные авторы: | , , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
MDPI AG
2020-01-01
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| Серии: | Information |
| Предметы: | |
| Online-ссылка: | https://www.mdpi.com/2078-2489/11/2/59 |
| Метки: |
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