Hybrid location-based recommender system for mobility and travel planning
In recent times, the modern developments of internet technologies and social networks have
attracted global researchers to explore the recommender systems for generating …
attracted global researchers to explore the recommender systems for generating …
An effective distributed predictive model with Matrix factorization and random forest for Big Data recommendation systems
Recommendation systems have been widely deployed to address the challenge of
overwhelming information. They are used to enable users to find interesting information from …
overwhelming information. They are used to enable users to find interesting information from …
Leveraging contextual influence and user preferences for point-of-interest recommendation
Abstract The effective Point-of-Interest (POI) recommendation can significantly assist users
to find their preferred POIs and help POI owners to attract more customers. As a result, a …
to find their preferred POIs and help POI owners to attract more customers. As a result, a …
A novel hotel recommendation method based on personalized preferences and implicit relationships
On tourism websites, hotel recommendations have drawn growing attention from
researchers, as they can help customers select a satisfactory hotel from many options with …
researchers, as they can help customers select a satisfactory hotel from many options with …
Ensemble-based Top-k recommender system considering incomplete data
Recommender systems have been widely used in e-commerce applications. They are a
subclass of information filtering system, used to either predict whether a user will prefer an …
subclass of information filtering system, used to either predict whether a user will prefer an …
How and when to stop the co-training process
Co-training is a semi-supervised learning approach used when only a small set of the data
that is available for training is labeled. By using multiple classifiers, the co-training process …
that is available for training is labeled. By using multiple classifiers, the co-training process …
Inductive conformal recommender system
Traditional recommendation algorithms can be used to develop techniques that can help
people choose desirable items of interest. However, in many real-world applications, it is …
people choose desirable items of interest. However, in many real-world applications, it is …
[PDF][PDF] Recommender System using Distributed Improved Predictive Framework with Matrix Factorization and Random Forest.
Online digital marketing achieves their revenue according to their advertisements or sales
assignment when companies have the profitable attention for recommending their products …
assignment when companies have the profitable attention for recommending their products …
“Furnish Your Reality”-Intelligent Mobile AR Application for Personalized Furniture
MD Do, N Dahlem, M Paulus, M Krick, L Steffny… - … Conference on Human …, 2024 - Springer
Today's online retailers are faced with the challenge of providing a convenient solution for
their customers to browse through a wide range of products. Simultaneously, they must meet …
their customers to browse through a wide range of products. Simultaneously, they must meet …
[HTML][HTML] Ensemble methods and semi-supervised learning for information fusion: A review and future research directions
Advances over the past decade at the intersection of information fusion methods and Semi-
Supervised Learning (SSL) are investigated in this paper that grapple with challenges …
Supervised Learning (SSL) are investigated in this paper that grapple with challenges …