基于电子商务的协同过滤推荐算法综述
A Research Summary of Collaborative Filtering Recommendation Algorithm Based on E-Commerce
摘要: 协同过滤推荐算法是目前电子商务推荐系统中应用场景最丰富也是使用最多的推荐算法。本文首先详细介绍了三种不同的协同过滤推荐算法并比较了各自的优势与不足，然后对协同过滤推荐算法目前存在的数据稀疏性、冷启动和可拓展性问题现有的研究现状进行了总结，并分析了现有的方法的可取与不足之处。最后提出了未来协同过滤算法的研究热点，为协同过滤算法未来发展提供参考。
Abstract: The collaborative filtering recommendation algorithm is the most abundant and most used recommendation algorithm in the current e-commerce recommendation system. This paper first introduces three different collaborative filtering recommendation algorithms in detail and compares their respective advantages and disadvantages. Then, the current research status of data sparseness, cold start and scalability of collaborative filtering recommendation algorithm is summarized. And this paper analyzes the merits and deficiencies of the existing methods. Finally, the research hotspot of future collaborative filtering algorithm is proposed, which provides a reference for the future development of collaborative filtering algorithm.
文章引用：俞立群, 王扶东. 基于电子商务的协同过滤推荐算法综述[J]. 电子商务评论, 2019, 8(1): 1-5. https://doi.org/10.12677/ECL.2019.81001

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