Secure artificial intelligence of things for implicit group recommendations
The emergence of Artificial Intelligence of Things (AIoT) has provided novel insights for
many social computing applications, such as group recommender systems. As the distances …
many social computing applications, such as group recommender systems. As the distances …
Towards latent context-aware recommendation systems
The emergence and penetration of smart mobile devices has given rise to the development
of context-aware systems that utilize sensors to collect available data about users in order to …
of context-aware systems that utilize sensors to collect available data about users in order to …
Deep learning and embedding based latent factor model for collaborative recommender systems
A collaborative recommender system based on a latent factor model has achieved
significant success in the field of personalized recommender systems. However, the latent …
significant success in the field of personalized recommender systems. However, the latent …
BPRH: Bayesian personalized ranking for heterogeneous implicit feedback
Personalized recommendation for online service systems aims to predict potential demand
by analysing user preference. User preference can be inferred from heterogeneous implicit …
by analysing user preference. User preference can be inferred from heterogeneous implicit …
A Survey on Recommendation Methods Based on Social Relationships
R Chen, K Pang, M Huang, H Liang, S Zhang, L Zhang… - Electronics, 2023 - mdpi.com
With the rapid development of online social networks recently, more and more online users
have participated in social network activities and rich social relationships are formed …
have participated in social network activities and rich social relationships are formed …
Towards the significance of taxi recommender systems in smart cities
R Katarya - Concurrency and Computation: Practice and …, 2023 - Wiley Online Library
Since their launch in the early 1990's, recommender systems (RSs) have played an
essential role in information filtering and providing personalized information to users by …
essential role in information filtering and providing personalized information to users by …
Efficient music recommender system using context graph and particle swarm
Music recommender systems is an important field of research because of easy availability
and use of online music. The most existing models only focus on explicit data like ratings …
and use of online music. The most existing models only focus on explicit data like ratings …
Learning adaptive trust strength with user roles of truster and trustee for trust-aware recommender systems
There are two key characteristics of users in trust relationships that have been well
studied:(1) users trust their friends with different trust strengths and (2) users play multiple …
studied:(1) users trust their friends with different trust strengths and (2) users play multiple …
Location perspective-based neighborhood-aware POI recommendation in location-based social networks
L Guo, Y Wen, F Liu - Soft Computing, 2019 - Springer
As an effective way to help users find attractive locations and meet their individual needs,
point-of-interest (POI) recommendation has become an important application in location …
point-of-interest (POI) recommendation has become an important application in location …
Group-based recurrent neural networks for POI recommendation
With the development of mobile Internet, many location-based services have accumulated a
large amount of data that can be used for point-of-interest (POI) recommendation. However …
large amount of data that can be used for point-of-interest (POI) recommendation. However …