Research commentary on recommendations with side information: A survey and research directions
Recommender systems have become an essential tool to help resolve the information
overload problem in recent decades. Traditional recommender systems, however, suffer …
overload problem in recent decades. Traditional recommender systems, however, suffer …
On-device recommender systems: A comprehensive survey
Recommender systems have been widely deployed in various real-world applications to
help users identify content of interest from massive amounts of information. Traditional …
help users identify content of interest from massive amounts of information. Traditional …
Recommendation systems: Algorithms, challenges, metrics, and business opportunities
Recommender systems are widely used to provide users with recommendations based on
their preferences. With the ever-growing volume of information online, recommender …
their preferences. With the ever-growing volume of information online, recommender …
Heterogeneous information network embedding for recommendation
Due to the flexibility in modelling data heterogeneity, heterogeneous information network
(HIN) has been adopted to characterize complex and heterogeneous auxiliary data in …
(HIN) has been adopted to characterize complex and heterogeneous auxiliary data in …
Leveraging meta-path based context for top-n recommendation with a neural co-attention model
Heterogeneous information network (HIN) has been widely adopted in recommender
systems due to its excellence in modeling complex context information. Although existing …
systems due to its excellence in modeling complex context information. Although existing …
[图书][B] Recommender systems
CC Aggarwal - 2016 - Springer
“Nature shows us only the tail of the lion. But I do not doubt that the lion belongs to it even
though he cannot at once reveal himself because of his enormous size.”–Albert Einstein The …
though he cannot at once reveal himself because of his enormous size.”–Albert Einstein The …
Learning graph-based poi embedding for location-based recommendation
With the rapid prevalence of smart mobile devices and the dramatic proliferation of location-
based social networks (LBSNs), location-based recommendation has become an important …
based social networks (LBSNs), location-based recommendation has become an important …
GeoMF: joint geographical modeling and matrix factorization for point-of-interest recommendation
Point-of-Interest (POI) recommendation has become an important means to help people
discover attractive locations. However, extreme sparsity of user-POI matrices creates a …
discover attractive locations. However, extreme sparsity of user-POI matrices creates a …
An experimental evaluation of point-of-interest recommendation in location-based social networks
Point-of-interest (POI) recommendation is an important service to Location-Based Social
Networks (LBSNs) that can benefit both users and businesses. In recent years, a number of …
Networks (LBSNs) that can benefit both users and businesses. In recent years, a number of …
Spatial-aware hierarchical collaborative deep learning for POI recommendation
Point-of-interest (POI) recommendation has become an important way to help people
discover attractive and interesting places, especially when they travel out of town. However …
discover attractive and interesting places, especially when they travel out of town. However …