Spectral clustering and embedding-enhanced POI recommendation in location-based social network

Spectral clustering and embedding-enhanced POI recommendation in location-based social network

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 clu...

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Bibliographic Details
Main Authors: Zhen LIU, Na’na WANG, Xiaodong WANG, Yongqi SUN
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2020-03-01
Series:Tongxin xuebao
Subjects:
location-based social network
POI recommendation
spectral clustering
spectral embedding
neural network
Online Access:http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020053/
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Summary: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.
ISSN:1000-436X

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