Results 1 to 10 of about 232 (178)
Enabling personalized smart tourism with location-based social networks [PDF]
PeerJ Computer ScienceWith the rapid advance of mobile internet, communication technology and the Internet of Things (IoT), the tourism industry is undergoing unprecedented transformation. Smart tourism offers users personalized and customized services for travel planning and
Yuqi Shen +4 more
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Information (Switzerland), 2017 Point-of-interest (POI) recommendation has been well studied in recent years. However, most of the existing methods focus on the recommendation scenarios where users can provide explicit feedback. In most cases, however, the feedback is not explicit, but
Jiang Haoran, Lei Guo
exaly +3 more sources
USER ACTIVITIES ANALYSIS IN LOCATION BASED SOCIAL NETWORK VIA ASSOCIATION RULES
ICTACT Journal on Soft Computing, 2021 In recent years, the field of the Internet of Things (IoT), including smart and wearable devices, has witnessed a tremendous advancement leading to the collection of a wide variety of information not only about users but also their activities via various
Yahia Belayadi +3 more
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SUDM-SP: A method for discovering trajectory similar users based on semantic privacy
High-Confidence Computing, 2023 With intelligent terminal devices’ widespread adoption and global positioning systems’ advancement, Location-based Social Networking Services (LbSNs) have gained considerable attention.
Weiqi Zhang, Guisheng Yin, Bingyi Xie
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RecPOID: POI Recommendation with Friendship Aware and Deep CNN
Future Internet, 2021 In location-based social networks (LBSNs), exploit several key features of points-of-interest (POIs) and users on precise POI recommendation be significant. In this work, a novel POI recommendation pipeline based on the convolutional neural network named
Sadaf Safavi, Mehrdad Jalali
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POI Neural-Rec Model via Graph Embedding Representation
Tsinghua Science and Technology, 2021 With the booming of the Internet of Things (IoT) and the speedy advancement of Location-Based Social Networks (LBSNs), Point-Of-Interest (POI) recommendation has become a vital strategy for supporting people’s ability to mine their POIs.
Kang Yang, Jinghua Zhu, Xu Guo
doaj +1 more source
Applied Sciences, 2020 The rapid development of location-based social networks (LBSNs) produces the increasing number of check-in records and corresponding heterogeneous information which bring big challenges of points-of-interest (POIs) recommendation in our daily lives.
Bin Xia +4 more
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Exploring Temporal and Spatial Features for Next POI Recommendation in LBSNs
IEEE Access, 2021 With the increasing popularity of Location-Based Social Networks (LBSNs), a significant volume of check-in data of users has been generated. Such massive data brings difficulties for the users to efficiently retrieve their desired point-of-interest (POI).
Miao Li +4 more
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SSTP: Social and Spatial-Temporal Aware Next Point-of-Interest Recommendation
Data Science and Engineering, 2023 The expansion of available information in location-based social networks (LBSNs) has led to information overload, making it urgent to discover users’ next point-of-interest (POI).
Junzhuang Wu +5 more
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Exploiting Two-Dimensional Geographical and Synthetic Social Influences for Location Recommendation
ISPRS International Journal of Geo-Information, 2020 With the rapid development of location-based social networks (LBSNs), because human behaviors exhibit specific distribution patterns, personalized geo-social recommendation has played a significant role for LBSNs.
Jiping Liu +4 more
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