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Point-of-Interest Recommendations
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016The emergence of Location-based Social Network (LBSN) services provides a wonderful opportunity to build personalized Point-of-Interest (POI) recommender systems. Although a personalized POI recommender system can significantly facilitate users' outdoor activities, it faces many challenging problems, such as the hardness to model user's POI decision ...
Huayu Li +3 more
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On successive point-of-interest recommendation
World Wide Web, 2018With the increasing popularity of location-based social networks (LBSNs), users are able to share the Point-of-Interests (POIs) they visited by check-ins. By analyzing the users’ historical check-in records, POI recommendation can help users get better visiting experience by recommending POIs which users may be interested in. Although recent successive
Yi-Shu Lu +4 more
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Point of Interest Recommendation via Tensor Factorization
2023In the recent era, recommendation systems have marked their footsteps and have changed the way of the travel industry. The recommendation system deals with massive amounts of data to identify users’ interests, making the location search easier. Many methods have been used so far for making predictions much more desirable regarding users’ interests by ...
Shreya Roy +2 more
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Context aware point of interest adaptive recommendation
Proceedings of the 2nd Workshop on Context-awareness in Retrieval and Recommendation, 2012Applications that allow the users to search for nearby points of interest have, recently, become very popular amongst mobile device users. However, the increasing amount of available information and the limitations of current mobile devices can hinder an efficient and helpful user experience. It is fundamental that what is shown to the user is relevant.
Paulo Pombinho +2 more
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Points of interest recommendation from GPS trajectories
International Journal of Geographical Information Science, 2015Recently, points of interest POIs recommendation has evolved into a hot research topic with real-world applications. In this paper, we propose a novel semantics-enhanced density-based clustering algorithm SEM-DTBJ-Cluster, to extract semantic POIs from GPS trajectories.
Yaqiong Liu, Hock Soon Seah
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APPR: Additive Personalized Point-of-Interest Recommendation
2018 IEEE Global Communications Conference (GLOBECOM), 2018Providing location recommendations has become an essential feature for location-based social networks (LBSNs), as it helps the users to explore new places and makes LBSNs more prevalent to them. Existing studies mostly focus on introducing the new features that affect users' check-in behaviours in LBSNs.
Elahe Naserianhanzaei +2 more
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Cold-start Point-of-interest Recommendation through Crowdsourcing
ACM Transactions on the Web, 2020Recommender system is a popular tool that aims to provide personalized suggestions to user about items, products, services, and so on. Recommender system has effectively been used in online social networks, especially the location-based social networks for providing suggestions for interesting places known as POIs (points-of-interest ...
Pramit Mazumdar +2 more
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A Geographical Behavior-Based Point-of-Interest Recommendation
2019 IEEE 5th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS), 2019With the development of mobile devices, point-of-interest (POI) recommendation has received increasing attention. However, achieving accurate personalized POI recommendation is challenging due to the sparsity of the available data per user. In addition, previous efforts based on collaborative filtering mainly treat user behavior as a whole part in ...
Xiaoyun Yu, Xin Li, Jidong Li, Keke Gai
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Recommendation of Points-of-Interest Using Graph Embeddings
2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA), 2018The rapid growth of Location-based Social Networks (LBSNs) has lead to the generation of massive datasets which are collected in an exponential rate. The collected information may be used to facilitate users' needs with recommendations related to their past preferences.
Giannis Christoforidis +3 more
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Points of Interest Recommendation Based on Context-aware
International Journal of Hybrid Information Technology, 2015Existing points of interest recommendation systems do not consider either spatial-temporal factors etc or the historic behavior of users. Though both of the two kinds of models have their strength, they don’t make evaluation for accuracy rate of POIs recommendation, especially recommendation Satisfaction Index (RSI) of users.
Fung Wong, Shijun Lee, Quanrui Wong
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