LBSN中融合信任与不信任关系的兴趣点推荐

doi:10.11959/j.issn.1000-436x.2018117

通信学报 ›› 2018, Vol. 39 ›› Issue (7): 157-165.doi: 10.11959/j.issn.1000-436x.2018117

LBSN中融合信任与不信任关系的兴趣点推荐

朱敬华(),明骞

黑龙江大学计算机科学与技术学院，黑龙江哈尔滨 150080

修回日期:2018-05-18 出版日期:2018-07-01 发布日期:2018-08-08
作者简介:朱敬华（1976-），女，博士，黑龙江大学教授、硕士生导师，主要研究方向为社会网络推荐、传感器网络、数据挖掘。|明骞（1991-），男，黑龙江大学硕士生，主要研究方向为基于位置社交网络的个性化推荐。
基金资助:
国家自然科学基金资助项目(61100048);国家自然科学基金资助项目(61370222);黑龙江省自然科学基金资助项目(F2016034)

POI recommendation by incorporating trust-distrust relationship in LBSN

Jinghua ZHU(),Qian MING

Department of Computer Science and Technology,Heilongjiang University,Harbin 150080,China

Revised:2018-05-18 Online:2018-07-01 Published:2018-08-08
Supported by:
The National Natural Science Foundation of China(61100048);The Natural Science Foundation of Heilongjiang Province(61370222);The National Natural Science Foundation of China(F2016034)

摘要/Abstract

摘要：

兴趣点（POI,point of interest）推荐是位置社交网络（LBSN,location-based social network）重要的个性化服务，广泛用于热门景点推荐和旅游线路规划等。传统的基于协同过滤的推荐算法根据用户相似性和位置相似性进行推荐，未考虑推荐用户与目标用户间的信任关系，而信任关系有助于提高推荐系统的准确性、顽健性和用户满意度。首先分析了信任与不信任关系的传播特征，然后给出了信任度的表示和计算方法，最后提出了融合用户相似性、地理位置相似性和信任关系的混合推荐模型。实验结果表明，与传统协同过滤推荐方法相比，融合信任关系的混合推荐方法显著提高了推荐结果的准确性和用户满意度。

关键词: 位置社交网络, 兴趣点推荐, 协同过滤, 信任关系

Abstract:

POI (point of interest) recommendation is an important personalized service in the LBSN (location-based social network) which has wide applications such as popular sights recommendation and travel routes planning.Most existing collaborative filter algorithms make recommendation according to user similarity and location similarity,they don’t consider the trust relationship between users.And trust relationship is helpful to improve recommendation accuracy,robustness and user satisfaction.Firstly,the propagation property of trust and distrust relationship was analyzed.Then,the measurement and computation method of trust were given.Finally,a hybrid recommendation system which combined user similarity,geographical location similarity and trust relationship was proposed.The experiments results show that the hybrid recommendation is obviously superior to the traditional collaborative filtering in terms of results accuracy and user satisfaction.

Key words: LBSN, POI recommendation, collaborative filtering, trust relationship

中图分类号:

TP311

朱敬华,明骞. LBSN中融合信任与不信任关系的兴趣点推荐[J]. 通信学报, 2018, 39(7): 157-165.

Jinghua ZHU,Qian MING. POI recommendation by incorporating trust-distrust relationship in LBSN[J]. Journal on Communications, 2018, 39(7): 157-165.

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LBSN中融合信任与不信任关系的兴趣点推荐

POI recommendation by incorporating trust-distrust relationship in LBSN

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