Results 21 to 30 of about 228 (183)
Session‐Based Graph Attention POI Recommendation Network
Point‐of‐interest (POI) recommendation which aims at predicting the locations that users may be interested in has attracted wide attentions due to the development of Internet of Things and location‐based services. Although collaborative filtering based methods and deep neural network have gain great success in POI recommendation, data sparsity and cold
Zhuohao Zhang +3 more
wiley +1 more source
User Model‐Based Personalized Recommendation Algorithm for News Media Education Resources
Traditional recommendations for news and media education resources usually ignore the importance of sequential patterns in user check‐in behavior and fail to effectively capture the complex and dynamically changing interests of users. As a result, this study provides a recommendation model for news and media education materials based on a user model ...
Zhu Shilin, Naeem Jan
wiley +1 more source
Aiming at the problems that the traditional model is difficult to extract information features, difficult to learn deep knowledge, and cannot automatically and effectively obtain features, which leads to the problem of low recommendation accuracy, this paper proposes a personalized tourism route recommendation model of intelligent service robot using ...
Xiang Huang, Shan Zhong
wiley +1 more source
Inferring Location Types With Geo-Social-Temporal Pattern Mining
With a rapid growth in the global population, the modern world is undergoing a rapid expansion of residential areas, especially in urban centres. This continuously demands for increased general services and basic amenities, which are required according ...
Tarique Anwar +5 more
doaj +1 more source
A POI Recommendation Algorithm Based on the Heterogeneous Graph Convolution Network
Point‐of‐interest (POI) recommendation is a type of recommendation task, which generates a list of places that users may be interested in. There is a complex heterogeneous graph structure between users and points of interest. The current recommendation algorithms are generally based on Euclidean space data, and the algorithms based on graph structure ...
Yue Li, Zhihan Liu
wiley +1 more source
Advances in Wireless Body Area Networks, where embedded accelerometers, gyroscopes, and other sensors empower users to track real‐time health data continuously, have made it easier for users to follow a healthier lifestyle. Various other apps have been intended to choose suitable physical exercise, depending on the current healthcare environment.
Sudhakar Sengan +6 more
wiley +1 more source
Interest Aware Location-Based Recommender System Using Geo-Tagged Social Media
Advances in location acquisition and mobile technologies led to the addition of the location dimension to Social Networks (SNs) and to the emergence of a newer class called Location-Based Social Networks (LBSNs). While LBSNs are richer in their model and
Basma AlBanna +3 more
doaj +1 more source
The POI recommendation system has become an important means to help people discover attractive and interesting places. Based on our data analysis, we observe that users pay equal attention to conservatism and curiosity. In particular, adopting analysis corresponding to different time intervals, we find that users lean towards old POIs in the short term
RuiChang Li, Yuyu Yin
wiley +1 more source
During the last decades, tourism has been augmented worldwide through which the diversity of tourists’ interests is increased and is challenging to tackle with the traditional management system.
Inayat Khan +5 more
doaj +1 more source
With the widespread use of the location-based social networks (LBSNs), the next point-of-interest (POI) recommendation has become an essential service, which aims to understand the user’s check-in behavior at the current moment by analyzing and mining ...
Jing Tian, Zilin Zhao, Zhiming Ding
doaj +1 more source

