Semantic Textual Similarity of Courses Based on Text Embeddings
Објеката
- Тип
- Рад у зборнику
- Верзија рада
- објављена
- Језик
- енглески
- Креатор
- Olivera Kitanović, Aleksandra Tomašević, Mihailo Škorić, Ranka Stanković, Ljiljana Kolonja
- Извор
- Lecture Notes in Networks and Systems
- Издавач
- Springer Nature Switzerland
- Датум издавања
- 2024
- Сажетак
- This paper explores the application of textual embeddings to measure semantic similarity between educational courses’ curriculums, aiming to enhance the effectiveness of the next faculty accreditation. Leveraging state-of-the-art natural language processing techniques, we employ pre-trained embeddings to capture the semantic meaning of course descriptions. Our methodology involves transforming course curriculum texts into high-dimensional vector representations, enabling efficient and meaningful comparisons. We evaluate the proposed approach on a diverse dataset of course descriptions, employing established benchmarks for semantic textual similarity . The results demonstrate the effectiveness of our method in capturing nuanced semantic relationships between courses.
- почетак странице
- 311
- крај странице
- 322
- doi
- 10.1007/978-3-031-71419-1_27
- issn
- 2367-3370
- Шира категорија рада
- М30
- Ужа категорија рада
- М33
- Права
- Затворени приступ
- Лиценца
- All rights reserved
- Формат
Olivera Kitanović, Aleksandra Tomašević, Mihailo Škorić, Ranka Stanković, Ljiljana Kolonja. "Semantic Textual Similarity of Courses Based on Text Embeddings" in Lecture Notes in Networks and Systems, Springer Nature Switzerland (2024). https://doi.org/10.1007/978-3-031-71419-1_27
This item was submitted on 9. јануар 2025. by [anonymous user] using the form “Рад у зборнику радова” on the site “Радови”: http://drug.rgf.bg.ac.rs/s/repo
Click here to view the collected data.