In E-commerce recommender system, collaborative filtering technology is the most popular and successful method at present.
电子商务推荐系统中协同过滤已成为目前应用最广泛、最成功的推荐方法。
Absrtact: In E- commerce recommender system, collaborative filtering technology is the most popular and successful method at present.
摘 要：电子商务推荐系统中协同过滤已成为目前应用最广泛、最成功的推荐方法。
Be inspired by the research achievement in e-commerce fields, we try to introduce the collaborative filtering technology into research of personalized recommendation of learning resources.
受电子商务研究领域中相关研究成果启发，我们尝试将协同过滤推荐技术引入学习资源的个性化推荐研究中。
This model of collaborative filtering technology is great help in the mitigation of existing sparse problems and recommendation in time.
该模型的建立对于缓解协同过滤技术中存在的稀疏性问题、推荐的实时性问题有很大的帮助。
Collaborative filtering technology reveals a number of bottlenecks to be addressed in the face of current challenges.
协同过滤技术在面对当前的挑战时暴露出许多有待解决的瓶颈问题。
Collaborative filtering technology reveals a number of bottlenecks to be addressed in the face of current challenges.
协同过滤技术在面对当前的挑战时暴露出许多有待解决的瓶颈问题。
应用推荐