计算机与现代化Issue(4)：74-78,5.DOI:10.3969/j.issn.1006-2475.2018.04.014
基于地理邻近性的自编码器在地点推荐中的应用
Geo-DAE for Point-of-interest Recommendation
摘要
Abstract
Personalized point-of-interest(POI)recommendation is crucial to the development of location-based social networks (LBSNs).It not only helps users explore new places but also enables third -party services to better provide service.Previous stud-ies on this topic treat all POIs as equal.Learning preferences within category makes sense,but the scale in which the frequency of check-ins operates is not comparable across categories.In this paper,we transform the check-in frequency into category-based preference according to TF-IDF theory.And then we propose a Geo-DAE model for the geographical proximity among POIs.The experimental results based on datasets from real-world LBSNs show that the proposed model achieves better performance than other state-of-the-art methods,and the proposed model is a better alternative for POI recommendation.关键词
地点推荐/自编码器/地理邻近性Key words
POI recommendation/auto encoder/geographical proximity分类
信息技术与安全科学引用本文复制引用
张文翔..基于地理邻近性的自编码器在地点推荐中的应用[J].计算机与现代化,2018,(4):74-78,5.基金项目
国家自然科学基金资助项目(71532009,71671121) （71532009,71671121）
