A novel group recommendation model with two-stage deep learning
Group recommendation has recently drawn a lot of attention to the recommender system
community. Currently, several deep learning-based approaches are leveraged to learn …
community. Currently, several deep learning-based approaches are leveraged to learn …
Recurrent knowledge graph embedding for effective recommendation
Knowledge graphs (KGs) have proven to be effective to improve recommendation. Existing
methods mainly rely on hand-engineered features from KGs (eg, meta paths), which …
methods mainly rely on hand-engineered features from KGs (eg, meta paths), which …
Latent relational metric learning via memory-based attention for collaborative ranking
This paper proposes a new neural architecture for collaborative ranking with implicit
feedback. Our model, LRML (Latent Relational Metric Learning) is a novel metric learning …
feedback. Our model, LRML (Latent Relational Metric Learning) is a novel metric learning …
An efficient group recommendation model with multiattention-based neural networks
Group recommendation research has recently received much attention in a recommender
system community. Currently, several deep-learning-based methods are used in group …
system community. Currently, several deep-learning-based methods are used in group …
Toward digital twin oriented modeling of complex networked systems and their dynamics: A comprehensive survey
This paper aims to provide a comprehensive critical overview on how entities and their
interactions in Complex Networked Systems (CNS) are modelled across disciplines as they …
interactions in Complex Networked Systems (CNS) are modelled across disciplines as they …
Discovering interpretable geo-social communities for user behavior prediction
Social community detection is a growing field of interest in the area of social network
applications, and many approaches have been developed, including graph partitioning …
applications, and many approaches have been developed, including graph partitioning …
Joint event-partner recommendation in event-based social networks
With the prevalent trend of combining online and offline interactions among users in event-
based social networks (EBSNs), event recommendation has become an essential means to …
based social networks (EBSNs), event recommendation has become an essential means to …
SOS: a multimedia recommender system for online social networks
Abstract The use of Online Social Networks has been rapidly increased over the last years.
In particular, Social Media Networks allow people to communicate, share, comment and …
In particular, Social Media Networks allow people to communicate, share, comment and …
A study on features of social recommender systems
Recommender system is an emerging field of research with the advent of World Wide Web
and E-commerce. Recently, an increasing usage of social networking websites plausibly …
and E-commerce. Recently, an increasing usage of social networking websites plausibly …
A collective bayesian poisson factorization model for cold-start local event recommendation
Event-based social networks (EBSNs), in which organizers publish events to attract other
users in local city to attend offline, emerge in recent years and grow rapidly. Due to the large …
users in local city to attend offline, emerge in recent years and grow rapidly. Due to the large …