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January 1, 2026International Journal of Technology Enhanced Learning

KashEnsem-R: a transformer-enhanced stacked ensemble framework for sentiment classification in Kashmiri

Sheezan Farooq Rumaan Bashir

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Key Points

This research aims to develop an effective framework for sentiment classification in the Kashmiri language using advanced AI methods.
Developed the KashEnsem-R framework incorporating transformer models and stacked ensemble techniques.
Evaluated the framework's performance on sentiment classification tasks within the Kashmiri language.
Achieved increased accuracy rates in sentiment classification compared to traditional methods.
Demonstrated superior performance metrics, enhancing understanding of sentiments in the Kashmiri language.

Implication

Evaluates sentiment classification accuracy in Kashmiri, suggesting improved performance with advanced technology.

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Cite This Study

Farooq et al. (2026) studied this question.

synapsesocial.com/papers/6a06b940e7dec685947abdb2 https://doi.org/10.1504/ijtel.2026.10078348

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