计算机科学 ›› 2018, Vol. 45 ›› Issue (8): 146-150.doi: 10.11896/j.issn.1002-137X.2018.08.026
张洪波, 王佳蕾, 张丽娟, 刘志宏
ZHANG Hong-bo, WANG Jia-lei, ZHANG Li-juan, LIU Zhi-hong
摘要： 经典的协同过滤推荐系统存在数据稀疏和冷启动问题。利用信任网络能够有效地解决此问题,但性能有待提高。根据“如果a信任b,则a与b相似度高的概率较大”这一普适规律,提出一种基于信任网络的协同过滤推荐算法。该算法采用惩罚、奖励机制,进一步提高了推荐系统的性能。算法将覆盖率和准确率作为衡量标准,与经典协同过滤算法和已有信任推荐算法进行实验对比,结果表明所提推荐方法的性能更好。
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