Identification of Relevant Scientific Articles using a Modified Naive Bayes Classifier

The rapid growth in the number of scientific publications increases researchers' need for systems that provide quick access to the most relevant articles on their subjects of interest. Existing solutions do not have enough flexibility to adapt to the needs of each user of the system. This study...

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Bibliographic Details
Published in2022 2nd International Conference on Technology Enhanced Learning in Higher Education (TELE) pp. 70 - 74
Main Authors Dvornikov, Dmitrii, Ilin, Dmitry, Kotilevets, Igor, Ivanova, Irina, Stepanova, Anna
Format Conference Proceeding
LanguageEnglish
Published IEEE 26.05.2022
Subjects
Analytical models
Data models
Education
machine learning
Naive Bayes
Naive Bayes methods
ranking model
text classification
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DOI10.1109/TELE55498.2022.9801050

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Summary:The rapid growth in the number of scientific publications increases researchers' need for systems that provide quick access to the most relevant articles on their subjects of interest. Existing solutions do not have enough flexibility to adapt to the needs of each user of the system. This study presents a scientific articles recommendation mechanism which takes into account the user's individual preferences. The precision of the recommendations is 70%.
DOI:10.1109/TELE55498.2022.9801050