Personal recommendation algorithm based on concept hierarchy
YE Yue-xiang · Jisuanji gongcheng · 2005
Collaborative filtering is the most successful technology for building recommendation systems. But with a large number of users and items, this method faces serious problems such as sparsity which makes the recommendation efficiency decline linearly. In this paper a concept hierarchy methodology ameliorating user-item matrix was suggested. By using buy-data and click-through-data and integrating items of similar users and those of multi-level association, this method showed good performance on sparsity set.