Analisis Sentimen: Pengaruh Jam Kerja Terhadap Kesehatan Mental Generasi Z by Muhammad Daffa Al Fahreza, Ardytha Luthfiarta, Muhammad Rafid, Michael Indrawan

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Stemming of Slovenian library science texts by Polona Vilar, Jasna Maver

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Processing morphological variants in searches of Latin text by Mark Greengrass, Alexander M. Robertson, Robyn Schinke, Peter Willett

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An annotated morphological dataset for Uzbek word forms: Towards rule-based and machine learning approachesMendeley Data by Nilufar Abdurakhmonova, Raima Shirinova, Rano Sayfullayeva, Davlatyor Mengliev, Bahodir Ibragimov, Manzura Ernazarova

“…Two morphological analysis approaches were implemented and compared: a user-defined rule-based stemming algorithm and a conditional random fields (CRF)-based machine learning model. …”
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Deep learning techniques for sentiment analysis in code-switched Hausa-English tweets by Yusuf Aliyu, Aliza Sarlan, Kamaluddeen Usman Danyaro, Abdullahi Sani abd Rahman, Aminu Aminu Muazu, Mustapha Yusuf Abubakar

“…This paper proposes an efficient hyperparameter tuning framework and a novel stemming algorithm for the Hausa language. The framework leverages word embeddings to determine the polarity scores of code-mixed tweets and enhances the accuracy of sentiment analysis models in low-resource language. …”
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Stemming as a basis for some non-conventional methods of information retrieval by Polona Vilar, Jure Dimec

“…Stemming is a process of text processing us¬ing stemming algorithms, the purpose of which is an automated selection of indexing terms used for content description. …”
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