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Category-Aware Location Embedding for Point-of-Interest Recommendation

Hossein A. Rahmani, Mohammad Aliannejadi, Rasoul Mirzaei Zadeh, Mitra Baratchi, Mohsen Afsharchi, Fabio Crestani
2019 Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval - ICTIR '19  
Recently, Point of interest (POI) recommendation has gained ever-increasing importance in various Location-Based Social Networks (LBSNs).  ...  Our model consists of a check-in module and a category module.  ...  Another line of research points out the importance of POI categories as they convey useful information regarding users' interests and habits [1, 2, 15] .  ... 
doi:10.1145/3341981.3344240 dblp:conf/ictir/RahmaniAZBAC19 fatcat:4fsj5ughivblbgvvtzseu7uupi

Embedding Taxonomical, Situational or Sequential Knowledge Graph Context for Recommendation Tasks [chapter]

Simon Werner, Achim Rettinger, Lavdim Halilaj, Jürgen Lüttin
2021 Applications and Practices in Ontology Design, Extraction, and Reasoning  
like time of day, weather or location and c) on the subjective individual history and experience of this user in preceding situations.  ...  Learned latent vector representations are key to the success of many recommender systems in recent years.  ...  LSTM-based Sequence-aware Recommendations As the basis for experiments with the LSTM network, we use the location embeddings that were acquired in the experiments from the section above.  ... 
doi:10.3233/ssw210046 fatcat:rfsad4zo7zhybdjloyor4zjczu

Personalized News Recommendation: Methods and Challenges [article]

Chuhan Wu, Fangzhao Wu, Yongfeng Huang, Xing Xie
2022 arXiv   pre-print
We then discuss the key points on improving the responsibility of personalized news recommender systems. Finally, we raise several research directions that are worth investigating in the future.  ...  Next, we introduce the public datasets and evaluation methods for personalized news recommendation.  ...  Besides, the location information of users is also very useful for accurate user modeling, and it has been used by several location-aware news recommendation methods [35, 114] .  ... 
arXiv:2106.08934v3 fatcat:iagqsw73hrehxaxpvpydvtr26m

A Survey on Deep Learning Based Point-Of-Interest (POI) Recommendations [article]

Md. Ashraful Islam, Mir Mahathir Mohammad, Sarkar Snigdha Sarathi Das, Mohammed Eunus Ali
2020 arXiv   pre-print
Huge volume of data generated from LBSNs opens up a new avenue of research that gives birth to a new sub-field of recommendation systems, known as Point-of-Interest (POI) recommendation.  ...  This review can be considered a cookbook for researchers or practitioners working in the area of POI recommendation.  ...  Problem Definition Point-of-Interest (POI) recommendation is a class of problems that suggest suitable future POIs for a user, given the historical check-in history of past users and other associated data  ... 
arXiv:2011.10187v1 fatcat:3uampnqerfdvnpuzrxcrsjviwq

Enhancing Traditional Local Search Recommendations with Context-Awareness [chapter]

Claudio Biancalana, Andrea Flamini, Fabio Gasparetti, Alessandro Micarelli, Samuele Millevolte, Giuseppe Sansonetti
2011 Lecture Notes in Computer Science  
This paper describes an approach to make context-aware mobile interaction available in scenarios where users might be looking for categories of points of interest (POIs), such as cultural events and restaurants  ...  , through remote location-based services.  ...  Evaluation We chose restaurants as popular points of interest users usually look for on mobile devices.  ... 
doi:10.1007/978-3-642-22362-4_29 fatcat:kaq4polelbcnrh7u2wz7obvkgy

CANS-Net: Context-Aware Non-Successive Modeling Network for Next Point-of-Interest Recommendation [article]

Qiang Cui, Yafeng Zhang, Jinpeng Wang
2021 arXiv   pre-print
Point-of-Interest (POI) recommendation is an important task in location-based social networks. It facilitates the sharing between users and locations.  ...  Recently, researchers tend to recommend POIs by long- and short-term interests.  ...  INTRODUCTION Location-based Social Networks (LBSNs), such as Foursquare, and Yelp, enable users to share check-in experiences and opinions on Point-of-Interests (POIs).  ... 
arXiv:2104.02262v1 fatcat:fncdk5n2ebfpvhj6mohl6fmey4

On-Device User Intent Prediction for Context and Sequence Aware Recommendation [article]

Benu Madhab Changmai, Divija Nagaraju, Debi Prasanna Mohanty, Kriti Singh, Kunal Bansal, Sukumar Moharana
2019 arXiv   pre-print
The knowledge of the user's real-time intention can help recommender systems to provide more relevant recommendations at the right moment. Our proposed algorithm is both context and sequence aware.  ...  Context-aware recommender systems typically handle large amounts of data which must be uploaded and stored on the cloud, putting the user's personal information at risk.  ...  Before recommending the next location the user is likely to visit, [6] first predicts the category of the location that the user would be interested in visiting.  ... 
arXiv:1909.12756v1 fatcat:yt3hurmdvnddfhazel3bcdiiae

How Far are We from Effective Context Modeling? An Exploratory Study on Semantic Parsing in Context

Qian Liu, Bei Chen, Jiaqi Guo, Jian-Guang Lou, Bin Zhou, Dongmei Zhang
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
We present a grammar-based decoding semantic parser and adapt typical context modeling methods on top of it.  ...  We evaluate 13 context modeling methods on two large complex cross-domain datasets, and our best model achieves state-of-the-art performances on both datasets with significant improvements.  ...  Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  ... 
doi:10.24963/ijcai.2020/491 dblp:conf/ijcai/ZhangSZLLWKK20 fatcat:ndayl3kevzhilgm7yg6garbpo4

DAN-SNR: A Deep Attentive Network for Social-Aware Next Point-of-Interest Recommendation [article]

Liwei Huang, Yutao Ma, Yanbo Liu, Keqing He
2020 arXiv   pre-print
Next (or successive) point-of-interest (POI) recommendation has attracted increasing attention in recent years.  ...  In this study, we discuss a new topic of next POI recommendation and present a deep attentive network for social-aware next POI recommendation called DAN-SNR.  ...  Ma is the corresponding author of this paper.  ... 
arXiv:2004.12161v1 fatcat:7ymnb4z4kndbrfkjwy35sy67aq

Exploring Temporal and Spatial Features for Next POI Recommendation in LBSNs

Miao Li, Wenguang Zheng, Yingyuan Xiao, Ke Zhu, Wei Huang
2021 IEEE Access  
Such massive data brings difficulties for the users to efficiently retrieve their desired point-of-interest (POI).  ...  (such as the current time and locations of the users).  ...  His research interests include computer architecture, embedded systems, and machine learning.  ... 
doi:10.1109/access.2021.3061502 fatcat:u4yfksypvfbg7em5ph7fkdrtje

Dynamic Recommendation of POI Sequence Responding to Historical Trajectory

Jianfeng Huang, Yuefeng Liu, Yue Chen, Chen Jia
2019 ISPRS International Journal of Geo-Information  
Point-of-Interest (POI) recommendation is attracting the increasing attention of researchers because of the rapid development of Location-based Social Networks (LBSNs) in recent years.  ...  In addition, two new metrics named Aligned Precision (AP) and Order-aware Sequence Precision (OSP) are proposed to evaluate the recommendation accuracy of a POI sequence, which considers not only the POI  ...  [28] also proposed an embedding-based method, called Content-Aware Hierarchical Point-of-Interest Embedding Model (CAPE), to utilize the text content that provides information about the characteristics  ... 
doi:10.3390/ijgi8100433 fatcat:rgrnkxkf3zdzfe2ur7rvu5l7pm

Relation Embedding for Personalised POI Recommendation [article]

Xianjing Wang, Flora D. Salim, Yongli Ren, Piotr Koniusz
2020 arXiv   pre-print
Point-of-Interest (POI) recommendation is one of the most important location-based services helping people discover interesting venues or services.  ...  To this end, we propose a translation-based relation embedding for POI recommendation.  ...  Acknowledgments We acknowledge the support of Australian Research Council Discovery DP190101485, Alexander von Humboldt Foundation, and CSIRO Data61 Scholarship program.  ... 
arXiv:2002.03461v2 fatcat:uscrnbl6qrdela3moehxtes7tq

Discovering Collaborative Signals for Next POI Recommendation with Iterative Seq2Graph Augmentation [article]

Yang Li, Tong Chen, Yadan Luo, Hongzhi Yin, Zi Huang
2022 arXiv   pre-print
Being an indispensable component in location-based social networks, next point-of-interest (POI) recommendation recommends users unexplored POIs based on their recent visiting histories.  ...  To overcome the sparsity of POI-level interactions, we further infuse category-awareness into SGRec with a multi-task learning scheme that captures the denser category-wise transitions.  ...  Introduction The fast growth of location-based social networks (LBSNs) facilitates the development of point-of-interest (POI) recommender systems, which help users explore attractive places by capturing  ... 
arXiv:2106.15814v2 fatcat:apyhlu3hkfdgtmtqelamu4ypei

Relation Embedding for Personalised Translation-Based POI Recommendation [chapter]

Xianjing Wang, Flora D. Salim, Yongli Ren, Piotr Koniusz
2020 Lecture Notes in Computer Science  
Point-of-Interest (POI) recommendation is one of the most important location-based services helping people discover interesting venues or services.  ...  To this end, we propose a translation-based relation embedding for POI recommendation.  ...  We acknowledge the support of Australian Research Council Discovery DP190101485, Alexander von Humboldt Foundation, and CSIRO Data61 Scholarship program.  ... 
doi:10.1007/978-3-030-47426-3_5 fatcat:zron5negfbea5lqfgnmz6rimuq

Exploring Student Check-In Behavior for Improved Point-of-Interest Prediction

Mengyue Hang, Ian Pytlarz, Jennifer Neville
2018 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining - KDD '18  
With the availability of vast amounts of user visitation history on location-based social networks (LBSN), the problem of Point-of-Interest (POI) prediction has been extensively studied.  ...  We also show how our learned embeddings could be used to identify similar students (e.g., for friend suggestions).  ...  Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notation hereon.  ... 
doi:10.1145/3219819.3219902 dblp:conf/kdd/HangPN18 fatcat:otcygqdcerffhlzagaxgtm23qe
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