| 1. | Research of personalized recommender system based on data mining on magnanimity data
基于海量数据挖掘的个性化推荐系统 |
| 2. | A survey of collaborative filtering algorithm applied in e - commerce recommender system
电子商务推荐系统中的协同过滤推荐 |
| 3. | An adaptive algorithm of collaborative filtering recommender based on aggregate - neighborhood
基于概念分层的个性化推荐算法 |
| 4. | On recommender ' s civil liability in the act of infringement of the recommended work
试论推荐人在推荐作品被认定侵权后的民事责任 |
| 5. | Model of collaborative filtering in e - commerce recommender system based on interest measure
基于兴趣度的协同过滤商品推荐系统模型 |
| 6. | An adaptive algorithm of collaborative filtering recommender based on correlation similarity
改进的基于相关相似性的协同过滤推荐算法 |
| 7. | Collaborative filtering is a successful technology that is implemented in e - commerce recommender systems today
协同过滤是目前在电子商务推荐系统中应用较为成功的个性化推荐技术。 |
| 8. | Also in the study of recommender system , we noticed mass marketing has been replaced by data - driven one to one marketing
此外在对推荐系统的研究中我们注意到，进入网络经济时代，大众营销策略已经没落。 |
| 9. | It gives emphasis to analyzing the problems which collaborative filtering is facing when it is applied in recommender systems and existing improved methods
着重分析了协同过滤在推荐系统中应用时所面临的问题，以及现有的解决方法。 |
| 10. | Web personalized recommender systems anticipate the needs of web users and provide them with recommendations according to their navigation patterns
Web个性化推荐系统根据用户的浏览模式预测用户需求,并向他们提供个性化的推荐服务。 |
