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- 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。
- Market Basket Analysis enables content affinity predictions even when cold-start situations obviate the relevance of collaborative filtering. 即便当冷启动状况回避了协同过滤的关联,市场篮分析启用内容亲缘性预测。
- Unlike all of the other engines, Item Affinity Engine recommendations are based on Market Basket Analysis statistics not collaborative filtering. 和其它所有引擎不同,项亲缘性推荐是基于市场篮分析统计信息而不是协同过滤。
- Oki, and Douglas Terry, Using collaborative filtering to weave an information tapestry, Communications of the ACM, Volume 35, Issue 12, pp61-70, 1992. 冯文正，合作式网站推荐系统，陀利交通大学信息科学研究所，民国89年。
- Empirical study has shown that our new model outperforms several other collaborative filtering models and algorithms remarkably. 实验表明新模型的预测结果明显优于其他几种协同过滤算法。
- Collaborative Filtering and Content-Based Filtering are techniques used in the design of recommender systems that support personalization. 推荐技术中的信息过滤系统包括内容过滤和协作过滤,纯粹的内容过滤系统和纯粹的协作过滤系统都存在各自的缺陷。
- Aiming at the difficulty of data sparsity in personalized recommendation systems, a new collaborative filtering algorithm using user background information was presented. 针对个性化推荐系统中协同过滤算法面对的数据稀疏问题，提出了一种结合用户背景信息的推荐算法。
- To overcome the difficulty of data sparsity in recommendation systems, a collaborative filtering (CF) algorithm based on clustering basal users is presented. 摘要为了降低数据稀疏性的影响，提高推荐系统的推荐生成质量，提出了一种基于多层相似性用户聚类的协同过滤推荐算法。
- The experimental results show that the improved algorithm can meliorate the recommendation quality of the collaborative filtering recommendation system. 实验表明，改进的算法提高了推荐系统的推荐质量。
- Collaborative filtering is one of the most successful technologies for building recommender systems, and is extensively used in many personalized systems. 摘要协同过滤算法是至今为止最成功的个性化推荐技术之一，被应用到很多领域中。
- All of them, collaborative filtering is regarded as most popular and successful personalized recommendatory algorithm in personalized recommendation system. 其中协同过滤被认为是至今为止在信息资源个性化推荐系统中最常用、最成功的一种个性化推荐技术。
- Experimental results show that this method is of low memory requirements and lower mean absolute error (MAE) value, and provides better recommendation quality compared with traditional collaborative filtering algorithms. 实验表明，这种方法的优点是低内存需求，具有较小的平均绝对偏差值，并且显示出了比传统推荐算法更好的推荐质量。
- To overcome the difficulty of the speed bottleneck of collaborative filtering (CF) algorithm used for generating recommendation, a CF algorithm based on clustering basal users is presented. 摘要为解决传统协同过滤算法在生成推荐时的速度瓶颈问题，提出了一种基于用户聚类的协同过滤推荐算法。
- A collaborative filtering recommendation algorithm based on clustering of items and customers is proposed, which combines clustering analysis with the collaborative filtering method. 摘要文章给出了一种基于项目与客户聚类的协同过滤推荐方法，将聚类分析与协同过滤方法紧密结合；
- Thesaurus concept hierarchy collaborative filtering algorithm improves search efficiency and quality of recommendatory results significantly which is proved by elementary test and analysis. 经过初步的测试分析，主题词概念分层协同过滤推荐算法可以显著的提高查询效率和推荐结果的质量。
- There are three common personalized recommendatory technologies: information retrieval and extractor, content-based filtering and collaborative filtering, data mining and knowledge discovery. 常用的个性化服务推荐技术包括三种：信息检索与信息抽取、基于内容的过滤和协同过滤、数据挖掘与知识发现。
- item-based Collaborative Filtering(CF) 基于项目的协作过滤
- Item-Based collaborative filtering Item-Based协同过滤
- Collaborative filtering recommendation 协同过滤推荐
- You need to filter the drinking water. 你需要把饮用水过滤。
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