计算机科学 ›› 2017, Vol. 44 ›› Issue (11): 164-167.doi: 10.11896/j.issn.1002-137X.2017.11.024
沈晶磊,虞慧群,范贵生,郭健美
SHEN Jing-lei, YU Hui-qun, FAN Gui-sheng and GUO Jian-mei
摘要： 如今随着推荐系统势头的加强,如何对用户行为进行快速而准确的预测变得愈加重要。通过分析网上社区帖子的点赞和点踩数据,实现了基于随机森林的推荐系统。该系统将实际问题转化为分类模型,并实现了数据处理、特征提取和参数调整。同时,该系统还对用户浏览帖子后是否产生交互行为进行了预测。最后,通过实验仿真并利用F1值对实验结果进行评估。实验结果证明了系统的有效性和效率。
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