位置社交网络中谱嵌入增强的兴趣点推荐算法

刘真; 王娜娜; 王晓东; 孙永奇

doi:10.11959/j.issn.1000-436x.2020053

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位置社交网络中谱嵌入增强的兴趣点推荐算法

学术通信 | 更新时间：2024-06-05

- 位置社交网络中谱嵌入增强的兴趣点推荐算法
- Spectral clustering and embedding-enhanced POI recommendation in location-based social network
- 通信学报 2020年41卷第3期页码：197-206
- 作者机构：
  
  北京交通大学计算机与信息技术学院，北京 100044
- 作者简介：
  
  [ "刘真（1977- ），女，江西南昌人，博士，北京交通大学副教授，主要研究方向为社会网络计算、推荐系统、大数据分析与挖掘" ]
  [ "王娜娜（1995- ），女，山东潍坊人，北京交通大学硕士生，主要研究方向为推荐系统、基于位置的社交网络" ]
  [ "王晓东（1995- ），男，湖北黄冈人，北京交通大学硕士生，主要研究方向为社交网络与社会计算" ]
  [ "孙永奇（1969- ），男，河南洛阳人，博士，北京交通大学教授，主要研究方向为大数据分析与挖掘、高性能计算" ]
- 基金信息：
  
  国家重点研发计划基金资助项目(2019YFB2102501)
- DOI：10.11959/j.issn.1000-436x.2020053
  中图分类号： TP391
- 网络首发：2020-03，
  
  纸质出版：2020-03-25
- 稿件说明：
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刘真, 王娜娜, 王晓东, 等. 位置社交网络中谱嵌入增强的兴趣点推荐算法[J]. 通信学报, 2020,41(3):197-206.

Zhen LIU, Na’na WANG, Xiaodong WANG, et al. Spectral clustering and embedding-enhanced POI recommendation in location-based social network[J]. Journal on Communications, 2020, 41(3): 197-206.
刘真, 王娜娜, 王晓东, 等. 位置社交网络中谱嵌入增强的兴趣点推荐算法[J]. 通信学报, 2020,41(3):197-206. DOI： 10.11959/j.issn.1000-436x.2020053.

Zhen LIU, Na’na WANG, Xiaodong WANG, et al. Spectral clustering and embedding-enhanced POI recommendation in location-based social network[J]. Journal on Communications, 2020, 41(3): 197-206. DOI： 10.11959/j.issn.1000-436x.2020053.

摘要

为了有效地捕捉LBSN中丰富的签到、社交等多维上下文信息的空间特性，并深层挖掘用户和POI之间的非线性交互，提出了一种谱嵌入增强的POI推荐算法——PSC-SMLP，设计了偏好增强的谱聚类算法PSC和谱嵌入增强的神经网络SMLP。在2个经典数据集上与现有的POI推荐算法相比，PSC-SMLP可以深层学习用户对POI的个性化偏好，在准确率、召回率、nDCG、平均精度等指标中均获得较大提升。

Abstract

In order to effectively capture the spatial characteristics of multi-dimensional context information in LBSN

and deeply explore the non-linear interaction between users and POIs

a spectral embedding enhanced POI recommendation algorithm

namely PSC-SMLP

was proposed.A preference enhanced spectral clustering algorithm (PSC) and a novel spectral embedded enhanced neural network (SMLP) was designed to solve the above problems.Compared with state-of-the-art algorithms on two datasets

PSC-SMLP has better performance in terms of the precision

recall

nDCG and mean average precision.

关键词

Keywords

references

刘树栋 , 孟祥武 . 基于位置的社会化网络推荐系统 [J ] . 计算机学报 , 2015 , 38 ( 2 ): 322 - 336 .

LIU S D , MENG X W . Recommender systems in location-based social networks [J ] . Journal of Computers , 2015 , 38 ( 2 ): 322 - 336 .

蒋仲安 , 王明 , 陈雅 . 基于地理坐标和轨迹数据的路径推荐方法 [J ] . 通信学报 , 2017 , 38 ( 5 ): 165 - 171 .

JIANG Z A , WANG M , CHEN Y . Path recommendation based on geographic coordinates and trajectory data [J ] . Journal of Communications , 2017 , 38 ( 5 ): 165 - 171 .

MOHAMMAD A , CRESTANI F . Personalized context-aware point of interest recommendation [J ] . ACM Transactions on Information Systems , 2018 , 36 ( 4 ):28.

LI X , GAO C , LI XL , et al . Rank-GeoFM:a ranking based geographical factorization method for point of interest recommendation [C ] // ACM Special Interest Group on International Retrieval . New York:ACM Press , 2015 : 433 - 442 .

LIAN D , ZHENG K , GE Y , et al . GeoMF++:scalable location recommendation via joint geographical modeling and matrix factorization [J ] . ACM Transactions on Information Systems , 2018 , 36 ( 3 ): 1 - 29 .

FAN W , LI Q , CHENG M . Deep modeling of social relations for recommendation [C ] // AAAI Conference on Artificial Intelligence . Palo Alto:AAAI Press , 2018 : 8075 - 8076 .

CHEN C , ZHANG M , WANG C , et al . An efficient adaptive transfer neural network for social-aware recommendation [C ] // ACM Special Interest Group on International Retrieval . New York:ACM Press , 2019 : 225 - 234 .

CHENG C , YANG H , KING I , et al . Fused matrix factorization with geographical and social influence in location-based social networks [C ] // AAAI Conference on Artificial Intelligence . Palo Alto:AAAI Press , 2012 : 1 - 8 .

ZHENG N , JIN X , LI L . Cross-region collaborative filtering for new point-of-interest recommendation [C ] // Proceedings of the 22nd International Conference on World Wide Web . New York:ACM Press , 2013 : 45 - 46 .

MA C , ZHANG Y , WANG Q , et al . Point-of-Interest recommendation:exploiting self-attentive auto encoders with neighbor-aware influence [C ] // Proceedings of the 27th ACM International Conference on Information and Knowledge Management . New York:ACM Press , 2018 : 697 - 706 .

ZHAO Z , YANG Q , LU H , et al . Learning max-margin geosocial multimedia network representations for point-of-interest suggestion [C ] // Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval . New York:ACM Press , 2017 : 833 - 836 .

YANG C , BAI L , ZHANG C , et al . Bridging collaborative filtering and semi-supervised learning:a neural approach for POI recommendation [C ] // Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining . New York:ACM Press , 2017 : 1245 - 1254 .

YING H , CHEN L , XIONG Y , et al . PGRank:personalized geographical ranking for point-of-interest recommendation [C ] // Proceedings of the 25th International Conference Companion on World Wide Web . New York:ACM Press , 2016 : 137 - 138 .

HE X , LIAO L , ZHANG H , et al . Neural collaborative filtering [C ] // Proceedings of the 26th International Conference Companion on World Wide Web . New York:ACM Press , 2017 : 173 - 182

ZHENG L , CHUN T L , JIANG F , et al . Spectral collaborative filtering [C ] // Proceedings of the 12th ACM Conference on Recommender Systems . New York:ACM Press , 2018 : 311 - 319 .

XIE M , YIN H , WANG H , et al . Learning graph-based POI embedding for location-based recommendation [C ] // Proceedings of the 25th ACM International on Conference on Information and Knowledge Management . New York:ACM Press , 2016 : 15 - 24 .

ZHANG J D , CHOW C Y . iGSLR:personalized geo-social location recommendation:a kernel density estimation approach [C ] // Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems . New York:ACM Press , 2013 : 334 - 343 .

WANG H , TERROVITIS M , MAMOULIS N . Location recommendation in location-based social networks using user check-in data [C ] // Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems . New York:ACM Press , 2013 : 374 - 383 .

ZHANG J D , CHOW C Y , LI Y . Lore:exploiting sequential influence for location recommendations [C ] // Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems . New York:ACM Press , 2014 : 103 - 112 .

YE M , YIN P , LEE W C , et al . Exploiting geographical influence for collaborative point-of-interest recommendation [C ] // Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval . New York:ACM Press , 2011 : 325 - 334 .

LIU Y , WEI W , SUN A , et al . Exploiting geographical neighborhood characteristics for location recommendation [C ] // Proceedings of the 23rd ACM International Conference on Information and Knowledge Management . New York:ACM Press , 2014 : 739 - 748

JONATHAN L H , JOSEPH A K , LOREN G T , et al . Evaluating collaborative filtering recommender systems [J ] . ACM Transactions on Information Systems , 2004 , 22 ( 1 ): 5 - 53 .

TANG J , HU X , GAO H , et al . Exploiting local and global social context for recommendation [C ] // Proceedings of the 23rd International Joint Conference on Artificial Intelligence . New York:ACM Press , 2013 : 2712 - 2718 .

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