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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| Published in | 2022 2nd International Conference on Technology Enhanced Learning in Higher Education (TELE) pp. 70 - 74 |
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| Main Authors | , , , , |
| Format | Conference Proceeding |
| Language | English |
| Published |
IEEE
26.05.2022
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| Subjects | |
| Online Access | Get full text |
| DOI | 10.1109/TELE55498.2022.9801050 |
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| Abstract | 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%. |
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| AbstractList | 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%. |
| Author | Stepanova, Anna Ivanova, Irina Dvornikov, Dmitrii Ilin, Dmitry Kotilevets, Igor |
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| SubjectTerms | Analytical models Data models Education machine learning Naive Bayes Naive Bayes methods ranking model text classification |
| Title | Identification of Relevant Scientific Articles using a Modified Naive Bayes Classifier |
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