计算机与现代化Issue(4)：23-26,4.DOI:10.3969/j.issn.1006-2475.2017.04.005
基于项目属性偏好的协同过滤算法
Collaborative Filtering Algorithm Based on Item Attribute Preference
摘要
Abstract
To tackle the data sparse problem of the traditional collaborative filtering algorithm, this paper proposes a collaborative filtering algorithm based on item attribute preference (CFBIAP).This algorithm calculates user similarity based on item attribute preference by using the item attributes and scores.Meanwhile it makes linear fitting with the similarity based on score matrix to get the user similarity.Up to a point, it decreases the error merely by score matrix partly.Experiments on MovieLens dataset show that the recommendation is better than traditional collaborative filtering algorithm both in quality and effect.The algorithm solves the data sparse problem effectively.关键词
协同过滤/推荐/项目属性/相似性Key words
collaborative filtering/recommendation/item attribute/similarity分类
信息技术与安全科学引用本文复制引用
朱明,魏慧琴..基于项目属性偏好的协同过滤算法[J].计算机与现代化,2017,(4):23-26,4.基金项目
国家自然科学基金"青年科学基金"资助项目(K11A800020) （K11A800020）
