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date:: 16-10-2020 publisher:: ACM place:: Virtual Event Canada conference-name:: MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems proceedings-title:: Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings isbn:: 978-1-4503-8135-2 doi:: 10.1145/3417990.3420202 title:: @Democratizing the development of recommender systems by means of low-code platforms pages:: 1-9 item-type:: ConferencePaper access-date:: 2023-05-17T09:27:46Z original-title:: Democratizing the development of recommender systems by means of low-code platforms language:: en url:: https://dl.acm.org/doi/10.1145/3417990.3420202 authors:: Claudio Di Sipio, Davide Di Ruscio, Phuong T. Nguyen library-catalog:: DOI.org (Crossref) links:: Local library, Web library

  • Abstract
    • In recent years, recommender systems have gained an increasingly crucial role in software engineering. Such systems allow developers to exploit a plethora of reusable artifacts, including source code and documentation, which can support the development activities. However, recommender systems are complex tools that are difficult to personalize or fine-tune if developers want to improve them for increasing the relevance of the retrievable recommendations.
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