Abstract
With the increasing development of Internet technology, the amount of data is increasing, and recommendation system has become the primary way to help users filter effective information from massive data. In the context of big data, how to apply relevant data to optimize recommendation algorithm has become the focus of current research. This paper mainly studies the big data personalized recommendation algorithm based on Hadoop e-commerce platform. This paper optimizes the object-based system filtering recommendation algorithm and builds a recommendation module using Hadoop platform. Hadoop technology is used to design a real-time recommendation system architecture to improve the real-time performance of the recommendation system. It can be seen from the simulation results in this paper that the hadoop-based recommendation algorithm is superior to the traditional recommendation algorithm in terms of accuracy, recall rate and F-score.
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Lv, L., Chen, Q. (2023). Big Data Personalized Recommendation Algorithm Based on Hadoop e-Commerce Platform. In: Hung, J.C., Yen, N.Y., Chang, JW. (eds) Frontier Computing. FC 2022. Lecture Notes in Electrical Engineering, vol 1031. Springer, Singapore. https://doi.org/10.1007/978-981-99-1428-9_98
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DOI: https://doi.org/10.1007/978-981-99-1428-9_98
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