| 基于加权Slope one的协同过滤个性化推荐算法 |
| |
| 引用本文： | 李桃迎,李墨,李鹏辉. 基于加权Slope one的协同过滤个性化推荐算法[J]. 计算机应用研究, 2017, 34(8) |
| |
| 作者姓名： | 李桃迎 李墨 李鹏辉 |
| |
| 作者单位： | 大连海事大学交通运输管理学院,大连海事大学交通运输管理学院,大连海事大学交通运输管理学院 |
| |
| 基金项目： | 国家科技支撑计划课题；国家社科基金项目；中央高校基本科研业务费 |
| |
| 摘 要： | 针对传统协同过滤算法存在冷启动、数据稀疏、运行效率低下等问题，分析了较传统协同过滤算法更加高效准确的Slope one算法的优点、原理及流程，针对Slope one算法未考虑用户兴趣变化和用户相似性这两方面的问题，提出了基于用户兴趣遗忘函数和用户最近邻居筛选策略的改进方案，以期提高推荐的质量，同时采用MovieLens数据集进行了实验验证，实验对比结果佐证了本文算法确实提高了推荐准确度并且减少了响应时间。
|
| 关 键 词： | 推荐算法；协同过滤；邻居选择；用户兴趣遗忘函数； |
| 收稿时间： | 2016-06-02 |
| 修稿时间： | 2017-04-12 |
Personalized collaborative filtering recommendation algorithm based on weighted Slope one |
| |
| Li Taoying,Li Mo and Li Penghui. Personalized collaborative filtering recommendation algorithm based on weighted Slope one[J]. Application Research of Computers, 2017, 34(8) |
| |
| Authors: | Li Taoying Li Mo Li Penghui |
| |
| Affiliation: | Transportation Management College of Dalian Maritime University,,Transportation Management College of Dalian Maritime University |
| |
| Abstract: | The traditional CF algorithm has the problem of data sparseness, cold start and low operation efficiency. This paper chooses slope one algorithm which is more efficient and accurate than traditional CF algorithm for research and analyses its advantages, principle and process.Shortcomings of slope one algorithm are pointed out that it does not take user interest changes and user similarity into account. This paper puts forward improved scheme of slope one algorithm based on user interest forgetting function and user nearest neighbors, proves the feasibility and better time performance of improved scheme by experimental test on MovieLens dataset. |
| |
| Keywords: | recommendation algorithm ?collaborative filtering neighbor-selection user interest forgetting function |
|
| 点击此处可从《计算机应用研究》浏览原始摘要信息 |
|
点击此处可从《计算机应用研究》下载全文 |
