融合推荐潜力的个性化趋势预测的混合推荐模型  

Hybrid recommendation model for personalized trend prediction of fused recommendation potential

作　　者：陈洪涛[1] 肖如良[1] 倪友聪[1] 杜欣[1] 龚平[1] 蔡声镇[1] 

机构地区：[1]福建师范大学软件学院,福州350108

出　　处：《计算机应用》2014年第1期218-221,共4页journal of Computer Applications

基　　金：教育部规划基金资助项目(11YJA860028);福建省科技计划重大项目(2011H6006)

摘　　要：预测用户对物品的行为中,准确的物品推荐是推荐系统的困难问题。为了提高推荐系统的推荐精度,引入物品的推荐潜力,提出一种新颖的融合物品推荐潜力的个性化混合推荐模型。首先根据最近短时间段和最近长时间段的物品访问率计算趋势动量,然后利用趋势动量计算出当前物品的推荐潜力值,最后将物品推荐潜力值融入到个性化推荐模型中得到混合推荐模型。实验证明,融合了物品推荐潜力值的个性化趋势预测,能较大地提高推荐系统的推荐精度。In recommendation system, it is difficult to predict the behavior of users on items and give the accurate recommendation. In order to improve the accuracy of recommendation system, the recommendation potential was introduced and a novel personalized hybrid recommendation model fused with recommendation potential was proposed. Firstly, the trend momentum was calculated according to the visits of items in recent short time and long time; then, the current recommendation potential was calculated utilizing trend momentum; finally, the hybrid recommendation model was achieved according to the fusion of recommendation potential and personalized recommendation model. The experimental results show that the personalized trend prediction fused with recommendation potential can improve the accuracy of recommendation system in a large scale.

关 键 词：推荐系统 混合推荐 推荐潜力 个性化 趋势预测 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]