工程科学学报Issue(2)：255-259,5.DOI:10.13374/j.issn2095-9389.2015.02.019
基于万有引力的个性化推荐算法
Gravitation-based personalized recommendation algorithm
摘要
Abstract
A recommendation algorithm is proposed by introducing the universal law of gravitation into a recommendation system. This new algorithm is named as the gravitation-based personalized recommendation ( GBPR) algorithm. In the algorithm, social tags used by users are regarded as particles that made up of their preference objects, social tags marking on items are considered as parti-cles that made up of item objects, and the user preference objects and item objects are taken as a user preference object model and an item object model, respectively. Gravitation exists between the user preference objects and item objects, and its strength obeys the universal law of gravitation. The strength of gravitation between the user preference objects and the item objects is computed, and it is regarded as their similarity. The bigger the strength is, the more similar they are, and the corresponding item objects are more proba-ble to be liked by users. Experimental results show that the proposed algorithm can get good performance.关键词
推荐算法/个性化/万有引力/社会标签Key words
recommendation algorithms/personalization/gravitation/social tags分类
信息技术与安全科学引用本文复制引用
王国霞,刘贺平,李擎..基于万有引力的个性化推荐算法[J].工程科学学报,2015,(2):255-259,5.基金项目
国家软科学研究计划资助项目(2013GXS5B178) （2013GXS5B178）
