基于用户兴趣的产品推荐算法研究  

Research on Product Recommendation Algorithm Based on User Interest

作　　者：徐叶军[1] XU Yejun(College of Biotechnology,Suzhou Industrial Park Institute of Services Outsourcing,Suzhou Jiangsu 215123,China)

机构地区：[1]苏州工业园区服务外包职业学院生物科技学院,江苏苏州215123

出　　处：《河北软件职业技术学院学报》2024年第3期1-3,共3页Journal of Hebei Software Institute

基　　金：苏州工业园区2022年度校企导师互聘“B类”人才(访问工程师)项目(BLRC202301)。

摘　　要：当前的产品推荐算法,用户兴趣指标较低,推荐质量不高。基于此,设计基于用户兴趣的产品推荐算法。该算法提取产品交易特征,规范用户对产品的认知度;基于用户兴趣计算产品特征相似性,增加用户感兴趣产品的推荐;构建产品推荐优化模型,优化产品推荐质量,进而实现产品的个性化推荐。通过实验的方式,验证了新算法的产品推荐效果更佳,极具推广价值。The current product recommendation algorithm has a low user interest indicator,and the quality of product recommendation decreases accordingly.Based on this,a product recommendation algorithm based on user interest is designed.Extracting product transaction features and standardizing user awareness of products;calculating product feature similarity based on user interest to increase the recommendation of products that users are interested in;constructing a product recommendation optimization model to optimize product recommendation quality,and thus achieving personalized product recommendation.Through experiments,it is verified that the new algorithm has better product recommendation performance and is highly valuable for promotion.

关 键 词：用户兴趣 农产品推荐 产品特征 推荐质量 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]