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基于用户与基于物品的协同过滤推荐算法
This project forked from scnuxiaotao/recom_sys
基于用户与基于物品的协同过滤推荐算法
1.抓到的数据最好是先使用id_change.java转化一下; 2.data为数据源; 3.src为java文件; 4.该工程为eclipse,如果不用的话直接把data的txt和src的java文件拿出来就可以了。 5.用户和物品推荐并不一定每个人都有推荐的结果出来,可能结果如下: PS:看不懂自己回去百度两个算法的原理 1)用户推荐: 看第6点,如果用户没有人关注ta则推荐不出来; 如果用户两人的相似度太低也不推荐(这个可以在程序中改一个变量,使他只要是关注的就推荐); 关注ta的人没有使用过物品(没有消费记录哪来推荐) 2)物品推荐: 用户用A物品,但是A物品没有相似的其他物品,故无推荐 6.用户推荐是基于社交网络的,根据关注A用户的人用过的物品来给A用户推荐。
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