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Advancing urban management: Integrating GIS, LLMs, and media narratives into environmental and socio-economic analyses for enhanced urban crime analysis. [PDF]

PLoS One
Cai Y, Chen A, Tang Z, Wang Y, Song Y.
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Achieving Pregnancy After Early Hormone Receptor-Positive Breast Cancer: Recent Evidence and Clinical Considerations. [PDF]

Cancers (Basel)
Ronan KE, Walshe JM.
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POI and Future Visitors Recommendation

2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2021
These days, Location-based Social Networks (LB-SNs) has gotten a lot of consideration in Point-of-Interest (POI) and future visitors Recommendation System. LBSNs has been utilized to mine client's verifiable data. Using the mined data, POI can be recommended to the client.
Grandhi Teja Sri Sai Suresh, K. Pushpak, Kothamasu Venkata Sivanaga Sai, Y. R. Abishake, C. P. Prathibhamol   +4 more
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Generic POI recommendation

Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers, 2020
For avoiding excessive congestion of tourists that causes overtourism, we propose a Generic Point of Interest (POI), which is an alternative sightseeing spot potentially attractive enough for tourists to replace a well-known sightseeing spot. We also propose a method to discover generic POIs and evaluate it.
Hisao Katsumi, Wataru Yamada, Keiichi Ochiai   +2 more
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Geographic-categorical diversification in POI recommendations

Proceedings of the 25th Brazillian Symposium on Multimedia and the Web, 2019
Nowadays, Recommender Systems (RSs) have been used to help users to discover relevant Points Of Interest (POI) in Location Based Social Network (LBSN), such as Yelp and FourSquare. Due to the main challenges of data sparsity and the geographic influence in this scenario, most of works about POI recommendations has only focused on improving the system's
Rodrigo Carvalho 0002, Nícollas Silva, Luiz Chaves, Adriano C. M. Pereira, Leonardo Rocha 0001   +4 more
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Exploiting Hierarchical Structures for POI Recommendation

2017 IEEE International Conference on Data Mining (ICDM), 2017
With the rapid development of location-based social networks, Point-of-Interest (POI) recommendation has played an important role in helping people discover attractive locations. However, existing POI recommendation methods assume a flat structure of POIs, which are better described in a hierarchical structure in reality.
Pengpeng Zhao 0001, Xiefeng Xu, Yanchi Liu, Ziting Zhou, Kai Zheng 0001, Victor S. Sheng, Hui Xiong 0001   +6 more
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Curriculum Meta-Learning for Next POI Recommendation

Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021
Next point-of-interest (POI) recommendation is a hot research field where a recent emerging scenario, next POI to search recommendation, has been deployed in many online map services such as Baidu Maps. One of the key issues in this scenario is providing satisfactory recommendation services for cold-start cities with a limited number of user-POI ...
Yudong Chen 0003, Xin Wang 0019, Miao Fan, Jizhou Huang, Shengwen Yang, Wenwu Zhu 0001   +5 more
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POI Recommendation Based on Heterogeneous Network

2020
With the development of wireless networks and positioning technologies, location-based social networks (LBSN) have gained popularity. More and more people share experiences about points of interest (POI) through “check-in” behavior. Mining the check-in data can help people discover the POI they are interested in.
Yan Wen 0002, Jiansong Zhang, Geng Chen 0002, Xin Chen 0079, Ming Chen 0001   +4 more
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A Multi-factor Recommendation Algorithm for POI Recommendation

2018
Point-of-Interest (POI) recommendation is an important service in Location-Based Social Networks (LBSNs). There are several approaches, such as collaborating filtering or content-based filtering, to solving the problem, but the quality of recommendation is low because of lack of personalized influencing factors for each user.
Rong Yang, Xiaofeng Han, Xingzhong Zhang
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POI Recommendation: A Temporal Matching between POI Popularity and User Regularity

2016 IEEE 16th International Conference on Data Mining (ICDM), 2016
Point of interest (POI) recommendation, which provides personalized recommendation of places to mobile users, is an important task in location-based social networks (LBSNs). However, quite different from traditional interest-oriented merchandise recommendation, POI recommendation is more complex due to the timing effects: we need to examine whether the
Zijun Yao 0001, Yanjie Fu, Bin Liu 0045, Yanchi Liu, Hui Xiong 0001   +4 more
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