Hanan A. Hosni Mahmoud1, Alaaeldin M. Hafez2, Eatedal Alabdulkreem1,*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 321-334, 2023, DOI:10.32604/iasc.2023.026235
- 06 June 2022
Abstract Languages–independent text tokenization can aid in classification of languages with few sources. There is a global research effort to generate text classification for any language. Human text classification is a slow procedure. Consequently, the text summary generation of different languages, using machine text classification, has been considered in recent years. There is no research on the machine text classification for many languages such as Czech, Rome, Urdu. This research proposes a cross-language text tokenization model using a Transformer technique. The proposed Transformer employs an encoder that has ten layers with self-attention encoding and a feedforward More >
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