摘要
由于现有的推荐系统未考虑生活场景随时间变化对购买行为的影响,本文提出基于生活场景的推荐系统。首先利用场景预测模型预测用户当前的生活场景,再结合该生活场景利用联合概率模型对候选产品打分排名,然后向该用户推荐相应的产品。针对生活场景特定领域,采用多元逻辑回归算法预测当前生活场景。实验结果表明,本文提出的基于生活场景的逻辑回归推荐算法提高了推荐精度。
Recently, the large impact of life stage on consumer＇ s purchasing behaviors has not taken into consideration. In this paper, we introduce a recommender system based on life-stage. Firstly, we label the life stage of the consumer by the model of lif-stage, then rank the candidate products with the predicted life stage by joint probability model and then recommend proper products. In the domain where the gap of the life stage is deterministic, we develop an efficient solution to do prediction using muhinomial logistic regression algorithm. Our experiment results show that the proposed approach improves the accuracy of the recommendation.
出处
《计算机与现代化》
2016年第12期38-41,共4页
Computer and Modernization
关键词
逻辑回归
时间效应
生活场景
logistic regression
time effect
life stage
