| 基于增量学习的混合推荐算法 |
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| 引用本文： | 任磊.基于增量学习的混合推荐算法[J].计算机应用,2010,30(5):1287-1289. |
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| 作者姓名： | 任磊 |
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| 作者单位： | 上海师范大学 |
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| 基金项目： | 上海市科委重大科技攻关计划项目(06DZ15008);;上海师范大学理工科项目(A-3101-10-033) |
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| 摘 要： | 推荐系统是自适应信息系统中的个性化服务模块，可以根据目标用户的信息需求提供个性化的信息服务。针对传统协作过滤算法存在的用户兴趣描述粒度过大问题，以及稀疏评分矩阵造成相似度计算不准确的问题，提出了一种基于增量学习的混合推荐算法WHHR，该算法通过Widrow-Hoff增量学习构建基于内容的用户模型，并结合协作过滤推荐机制实现评分预测。实验验证了WHHR算法在收敛速度和推荐准确性方面较类似推荐算法有较大提高。
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| 关 键 词： | 混合推荐算法 增量学习 用户建模 基于内容的过滤 协作过滤 |
| 收稿时间： | 2009-10-25 |
| 修稿时间： | 2009-12-04 |
Hybrid recommendation approach based on incremental learning |
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| REN Lei.Hybrid recommendation approach based on incremental learning[J].journal of Computer Applications,2010,30(5):1287-1289. |
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| Authors: | REN Lei |
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| Affiliation: | 1.Department of Computer Science/a>;Shanghai Normal University/a>;Shanghai 200234/a>;China/a>;2.Department of Computer Science/a>;East China Normal University/a>;Shanghai 200062/a>;China |
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| Abstract: | Recommendation is a kind of personalized service in the adaptive information system,and it can provide personalized information according to individual information needs.Concerning the issues of the user profiling granularity and the sparsity of user-item matrix in the classical collaborative filtering,a hybrid recommendation approach named WHHR was proposed based on incremental learning.WHHR implemented user modeling with Widrow-Hoff learning and predicted ratings by collaborative filtering.The experimenta... |
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| Keywords: | hybrid recommender approach incremental learning user profiling content-based filtering collaborative filtering |
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