Collaborative Filtering

Traditional collaborative filtering algorithm is a weighted average prediction algorithm based on nearest neighbors'ratings.

传统协同过滤算法最后的预测值是用户最近邻评价的加权平均值,过于强调相似度的作用.

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Research on Campus Educational Resources' Personalized Recommendation Based on Collaborative Filtering

基于协同过滤的校园教育资源网个性化推荐研究

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Collaborative filtering is a widely used technology of personalized recommendation systems.

协同过滤算法是目前应用广泛的一种个性化推荐技术，传统的协同过滤算法又分为基于用户和基于项目的协同过滤。

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A new intelligent recommendation system is presented based on Web service by Item-to-Item collaborative filtering algorithm. And the effectivity of the algorithm and the recommendation system is validated by an instance research as the relevant experiment result.

提出了一种基于Web服务的智能网页推荐系统，该系统使用了基于Item-to-Item的协同过滤算法，并通过对一个实例的研究验证了所提出的算法以及推荐系统的有效性。

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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

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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非线性滤波的迫近

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In order to serve users with more accurate information, the Agent collaborative filtering model& ACFM based on users 'feedback and the dynamic Q learning algorithm are put forward, and users' interesting model is built.

为了提供给用户更准确的信息，提出基于用户反馈的智能合作过滤模型和一种基于用户兴趣的动态Q学习算法，并建立用户兴趣模型。

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Collaborative filtering is the most widely used and most successful recommendation technology.

协同过滤是推荐系统中采用最为广泛也是最为成功的推荐技术。

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The major work done is reflected in the following areas: This thesis has analyzed the shortcomings of collaborative filtering algorithms, and proposed the combined recommendation algorithm of collaborative filtering algorithms which is based on item attributes.

本文所做的主要的工作体现在下面的几个方面：分析了协同过滤算法缺点，针对其缺点提出基于项目属性矩阵的协同过滤的组合推荐算法。

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Then, it proposed a user-feature-based recommendation algorithm and an improved item-based collaborative filtering algorithm, which to some extent alleviate the major challenges the recommender system are facing.

在此基础上，提出了基于用户特征的推荐算法和改进的基于项目的协同过滤算法，从而在一定程度上缓解了推荐系统面临的主要挑战。

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