But, with expansion of E-commerce system's size, collaborative filtering approach suffer from many challenges, for instance, quality of recommendations, scalability, sparsity, cold-start problem.
电子商务系统规模的日益扩大，协同过滤推荐方法也面临诸多挑战：推荐质量、可扩展性、数据稀疏性、冷开始问题等等。
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。
Collaborative Commerce, flow management and Workflow technology are the hotspots of E-business, management idea and computer application research.
协同商务、流程管理和工作流技术是电子商务、管理思想和计算机应用领域研究的热点。
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。
Collaborative filtering is thriving among lots of personalized recommendation technology which leads the recommendation system trends of major e-commerce platforms.
众多个性化推荐技术中协同过滤可谓一枝独秀，该算法引领了当今各大电子商务平台的推荐系统的发展趋势。
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。
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。
应用推荐