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Received:May 27, 2011 Revised:July 07, 2011
Received:May 27, 2011 Revised:July 07, 2011
中文摘要: 为解决“新用户”和“稀疏性”问题,引入商品基因的概念,通过将商品基因库、用户历史行为库、用户在线浏览内容及邻近用户行为数据耦合,形成用户偏好度候选集的兴趣模式抽取模块,然后利用改进的遗传算法优化模块进行模式选取与聚合,完成最优邻居的选择,最后经由推荐模块产生最终的推荐项目集。实验结果表明,提出的算法提高了推荐的准确度和覆盖面。
Abstract:(Department of Transportation Engineering, Huaiyin Institute of Technology, Huai'an 223003, China)
文章编号： 中图分类号： 文献标志码：
基金项目:
| Author Name | Affiliation |
| ZHANG Hao | Department of Transportation Engineering, Huaiyin Institute of Technology, Huai'an 223003, China |
| Author Name | Affiliation |
| ZHANG Hao | Department of Transportation Engineering, Huaiyin Institute of Technology, Huai'an 223003, China |
引用文本：
张浩.基于商品基因和遗传算法的个性化推荐系统.计算机系统应用,2011,20(12):114-117,166
ZHANG Hao.Personalized Recommendation System Based on Commodity Gene and GA.COMPUTER SYSTEMS APPLICATIONS,2011,20(12):114-117,166
张浩.基于商品基因和遗传算法的个性化推荐系统.计算机系统应用,2011,20(12):114-117,166
ZHANG Hao.Personalized Recommendation System Based on Commodity Gene and GA.COMPUTER SYSTEMS APPLICATIONS,2011,20(12):114-117,166
