Using an explicit query and a topic model for scientific article recommendation
Author:
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Education
Link
https://link.springer.com/content/pdf/10.1007/s10639-023-11817-2.pdf
Reference24 articles.
1. Adomavicius, G. & Tuzhilin, A. (2005). Toward the next generation of recommender systems : a survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering, 17(6). https://doi.org/10.1109/TKDE.2005.99
2. Albalawi, R., Yeap, T. H. & Benyoucef, M. (2020). Using Topic Modeling Methods for Short-Text Data : A Comparative Analysis. Frontiers in artificial intelligence, 3. https://doi.org/10.3389/frai.2020.00042
3. Almonte, L., Guerra, E., Cantador, I., & de Lara, J. (2022). Recommender systems in model-driven engineering. Software and Systems Modeling, 21, 249–280. https://doi.org/10.1007/s10270-021-00905-x
4. Amami, M., Pasi, G., Stella, F., & Faiz, R. (2016). An LDA-based approach to scientific paper recommendation. In Springer eBooks (pp. 200–210). Springer Nature. https://doi.org/10.1007/978-3-319-41754-7_17
5. Bagul, D., & Barve, S. (2021). A novel content-based recommendation approach based on LDA topic modeling for literature recommendation. International Conference on Inventive Computation Technologies. https://doi.org/10.1109/icict50816.2021.9358561
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