Please use this identifier to cite or link to this item:
Title: Spatial-temporal distance metric embedding for time-specific POI recommendation
Authors: Ding, Ruifeng
Chen, Zhenzhong
Li, Xiaolei
Keywords: Location-based Social Networks
DRNTU::Engineering::Computer science and engineering
Time-specific POI Recommendation
Issue Date: 2018
Source: Ding, R., Chen, Z., & Li, X. (2018). Spatial-temporal distance metric embedding for time-specific POI recommendation. IEEE Access, 6, 67035-67045. doi: 10.1109/ACCESS.2018.2869994
Series/Report no.: IEEE Access
Abstract: With the growing popularity of location-based social networks (LBSNs), time-specific POI recommendation has become important in recent years, which provides more accurate recommendation services for users in specific spatio–temporal contexts. In this paper, we propose a spatio–temporal distance metric embedding model (ST-DME) for time–specific recommendation, which exploits both temporal and geo-sequential property of a check-in to effectively model users’ time-specific preferences. Specifically, we divide timestamps of user’ check-ins into different time slots and adopt Euclidean distance rather than inner product of latent vectors to measure users’ preferences for POIs in a given time slot. We also apply a transition coefficient based on users’ most recent check-ins to incorporate geo-sequential influence in users’ check-in behaviors. A weighted pairwise loss with a hard sampling strategy is adopted to optimize latent vectors of users, POIs, and time slots in a metric space. Extensive experiments are conducted to demonstrate the effectiveness of our proposed method and results show that ST-DME outperforms state-of-the-art algorithms for time-specific POI recommendation on two public LBSNs data sets.
Rights: © 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See for more information.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

Files in This Item:
File Description SizeFormat 
Spatial-Temporal Distance Metric Embedding for Time-Specific POI Recommendation.pdf1.41 MBAdobe PDFThumbnail

Google ScholarTM



Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.