Description: It is a document which is very new today, It discribe recommender System that use trust technique in Recommender System! Platform: |
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Author:gau |
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Description: 在网络和电子商务环境下,推荐系统得到了广泛的应用。本文在建立了推荐系统的研究内容框架的基础上,从用户信息收集和用户建模、个性化推荐算法、推荐系统的评价及推荐系统的应用等四个方面对推荐系统的现有研究成果进行了系统的评述,并指出了推荐系统未来研究热点和发展方向。
-【英文摘要】 Recommender systems are among the most typical outcomes of the Internet and E-commerce.In this paper, the authors point out research contents of recommender systems.Then,some critical techniques related are discussed from the following four aspects:data collection and modeling,recommendation algorithms,recommender systems evaluation and recommender systems applications.In the end,the authors present their perspectives on the future and challenges in recommender system studies.
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Size: 470016 |
Author:1f |
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Description: 随着网络信息的不断增长，人们想要从中获得有用的信息变的越来越难，因此推荐系统应运而生-With the network information is growing, people want to get useful information from becoming more and more difficult, so the system came into being recommended Platform: |
Size: 464896 |
Author:王彬 |
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Description: 基于JSP的电子商务网站商品推荐系统的设计与开发-JSP commodity recommendation system of e-commerce website design and development
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Author:小林竹子 |
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Description: 面向下一代的推荐系统，推荐系统综述。入门必看（英文版）-For next generation recommender system to recommend a systematic review. Entry must see (English) Platform: |
Size: 470016 |
Author:fs |
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Description: 【转】协同过滤代码，用于推荐系统，包括基于项目和基于用户两种情况。实现基于用户和基于项目的协同过滤算法。 实验所用数据为MovieLens – a web-based movies recommender system with 43,000 users & over 3500 movies. 保存在ga.mat文件用，由于ga.test测试集过于庞大，全部用来计算的话耗时庞大，所以每次计算时随机选择部分，具体函数的使用请参照probar.m。我所得到的实验结果保存在results1-results8.mat里面。-[Turn] collaborative filtering code for the recommended system, including project-based and user-based two cases. User-based and project-based collaborative filtering algorithm. Experimental data for MovieLens- a web-based movies recommender system with 43,000 users & over 3500 movies. Saved in ga.mat file with Because ga.test test set is too large, all used to calculate the time-consuming massive, so every time The calculated random selection portion, the use of the specific function, please refer to probar.m. I obtained experimental results are saved inside results1-results8.mat. Platform: |
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Author:Singel |
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Description: This is a demo code to illustrate application of
blind compressive sensing framework to
recommender system design (to predict users
choice for items). Platform: |
Size: 3072 |
Author:backspacekb |
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Description: Collaborative Filtering，基于Collaborative Filtering，建立主动为用户推荐商品的推荐系统。实现参考协同过滤算法或它的优化，实现并改进算法，计算出每个客户对未购买的商品的兴趣度，并向客户主动推荐他最感兴趣的N个商品。实验数据可以从MovieLens.com下载。要求使用至少10，000不同用户的数据，至少1000个不同的movie。-Collaborative Filtering，Based Collaborative Filtering, the initiative for the establishment of user recommended product recommendation system. Reference implementation or its collaborative filtering algorithm optimized to achieve and improve the algorithm to calculate each customer not purchased the degree of interest to the customer the initiative to recommend N of products he is most interested. Experimental data can be downloaded MovieLens.com. It requires the use of at least 10,000 different user data, at least 1,000 different movie. Platform: |
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Author:way |
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Description: 这是一本关于推荐系统的经典书籍，便于入门，操作性强，值得一读。-This is a classic book on the recommendation system, easy to start, operational, it is worth reading. Platform: |
Size: 11816960 |
Author:猫熊 |
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Description: 基于多种算法的推荐系统python实现，其中包括了SVD、聚类分析等多种热门算法，并且有很强的可扩展性(A recommender system based on several kinds of algorithms, written in python) Platform: |
Size: 9560064 |
Author:WZY_Ken
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Description: cos相似度实现推荐预测，实现了找出相似度最大的某行某列进行预测(Cos similarity to achieve the recommended prediction, to achieve the largest similarity to find a row of a column to predict) Platform: |
Size: 212992 |
Author:逃课大神
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Description: The Reperio engine is a flexible and generic hybrid recommender system designed during the Platform: |
Size: 4533248 |
Author:Faiz23
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Description: 这是用Python写的一个电影推荐系统，希望对他人有帮助。(This is a movie recommendation system written in Python, I hope it will be helpful to others.) Platform: |
Size: 1631232 |
Author:krx07140162 |
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