A collaborative filtering recommendation algorithm based on biclustering
文献类型：会议论文
| 作者 | Wang JS(汪家升) ; Song H(宋宏); Zhou XF(周晓锋)
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| 出版日期 | 2015 |
| 会议名称 | 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER) |
| 会议日期 | June 8-12, 2015 |
| 会议地点 | Shenyang, China |
| 关键词 | collaborative filtering recommender system biclustering data sparsity |
| 页码 | 803-807 |
| 中文摘要 | Collaborative filtering has been widely used in many fields such as movie recommendation and e-commerce. However, there are still some problems such as data sparsity which restrict its further development. To address the data sparsity problem we proposed a novel collaborative filtering recommendation algorithm based on biclustering. Firstly, we use biclustering algorithm simultaneous clustering of the rows and columns of the rating matrix to generate biclusters, then the missing data can be smoothed by using the information of the biclusters. Secondly, a weighted matrix is introduced to distinguish between the original data and the smoothing data. Lastly, the active user's neighbors can be found based on the new similarity we proposed, and the recommendation to the active user is produced. The experiment results are offered, which show that the algorithm we presented can alleviate the data sparsity problem and improve the quality of the recommendation. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 1 |
| 会议录 | 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
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| 会议录出版者 | IEEE |
| 会议录出版地 | Piscataway, NJ, USA |
| 语种 | 英语 |
| ISSN号 | 2379-7711 |
| ISBN号 | 978-1-4799-8730-6 |
| WOS记录号 | WOS:000380502300153 |
| 源URL | [http://ir.sia.cn/handle/173321/17356]  |
| 专题 | 沈阳自动化研究所_数字工厂研究室 |
| 推荐引用方式 GB/T 7714 | Wang JS,Song H,Zhou XF. A collaborative filtering recommendation algorithm based on biclustering[C]. 见:2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER). Shenyang, China. June 8-12, 2015. |
入库方式： OAI收割
来源：沈阳自动化研究所
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