Collaborative filtering-based recommendation system for big data
| العنوان: | Collaborative filtering-based recommendation system for big data |
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| المؤلفون: | Lina Chen, Jian Shen, Tianqi Zhou |
| المصدر: | International Journal of Computational Science and Engineering. 21:219 |
| بيانات النشر: | Inderscience Publishers, 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Focus (computing), Information retrieval, Java, business.industry, Computer science, Big data, E-commerce, Recommender system, Computational Mathematics, Computational Theory and Mathematics, Hardware and Architecture, Modeling and Simulation, Collaborative filtering, business, computer, Software, Reliability (statistics), computer.programming_language |
| الوصف: | Collaborative filtering algorithm is widely used in the recommendation system of e-commerce website, which is based on the analysis of a large number of users' historical behaviour data, so as to explore the users' interest and recommend the appropriate products to users. In this paper, we focus on how to design a reliable and highly accurate algorithm for movie recommendation. It is worth noting that the algorithm is not limited to film recommendation, but can be applied in many other areas of e-commerce. In this paper, we use Java language to implement a movie recommendation system in Ubuntu system. Benefiting from the MapReduce framework and the recommendation algorithm based on items, the system can handle large datasets. The experimental results show that the system can achieve high efficiency and reliability in large datasets. |
| تدمد: | 1742-7193 1742-7185 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2c7b003d4d984ff25105ec8bb5f1bc13Test https://doi.org/10.1504/ijcse.2020.10027426Test |
| رقم الانضمام: | edsair.doi.dedup.....2c7b003d4d984ff25105ec8bb5f1bc13 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 17427193 17427185 |
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