Results 171 to 180 of about 2,209 (219)

Multi-Graph Convolutional Network for Fine-Grained and Personalized POI Recommendation

Electronics (Switzerland), 2022
With the advent of the era of rapid information expansion, the massive data backlog that exists on the Internet has led to a serious information overload problem, which makes recommendation systems a crucial part of human life.
Suzhi Zhang, Zijian Bai, Pu Li
exaly   +2 more sources

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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
openaire   +1 more source

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
openaire   +1 more source

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
openaire   +1 more source

On accurate POI recommendation via transfer learning

Distributed and Parallel Databases, 2020
Point of interest (POI) recommendation is of great value for both service providers and users. However, it is hard due to data scarcity. To this end, in this paper, we propose a transfer learning based deep neural model, which fuses valueable cross-domain knowledge to achieve more accurate POI recommendation.
Hao Zhang, Siyi Wei, Xiaojiao Hu, Ying Li, Jiajie Xu 0001   +4 more
openaire   +1 more source

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
openaire   +1 more source

Clustering Users’ POIs Visit Trajectories for Next-POI Recommendation

2018
A novel recommender system that supports tourists in choosing interesting and novel points of interests (POIs) is here presented. It can deal with situations where users’ data is scarce and there is no additional information about users apart from their past POIs visits.
David Massimo, Francesco Ricci 0001
openaire   +1 more source

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
openaire   +1 more source

Property Analysis of Stay Points for POI Recommendation

2021
Stay points extracted from trajectories are often treated as points of interest (POI) in the data preprocessing of POI recommendations. Popularity (i.e., the number of visits) is one of the important features to distinguish the value of different POIs, especially for tourists traveling in an unfamiliar city.
Junjie Sun, Yuta Matsushima, Qiang Ma 0001   +2 more
openaire   +1 more source

POI recommendation with geographical and multi-tag influences

2016 International Conference on Behavioral, Economic and Socio-cultural Computing (BESC), 2016
In this paper, we propose a method for point of interest (POI) recommendation by extracting the multi-tag influence and modeling the geographical influence. First of all, we extract a user-tag matrix from the initial user-POI rating matrix by analyzing the relations between POI and the related bag of tags.
Zhiyuan Zhang 0003, Yun Liu 0001, Haiqiang Chen, Qing Liu 0001   +3 more
openaire   +1 more source