Progress in context-aware recommender systems—An overview
Recommender Systems are the set of tools and techniques to provide useful
recommendations and suggestions to the users to help them in the decision-making process …
recommendations and suggestions to the users to help them in the decision-making process …
A novel social network hybrid recommender system based on hypergraph topologic structure
With the advent and popularity of social network, more and more people like to share their
experience in social network. However, network information is growing exponentially which …
experience in social network. However, network information is growing exponentially which …
Employing singular value decomposition and similarity criteria for alleviating cold start and sparse data in context-aware recommender systems
KV Rodpysh, SJ Mirabedini, T Banirostam - Electronic Commerce …, 2023 - Springer
The recommender system's primary purpose is to estimate the user's desire and provide a
list of items predicted from the appropriate information. Also, context-aware recommendation …
list of items predicted from the appropriate information. Also, context-aware recommendation …
Cold item integration in deep hybrid recommenders via tunable stochastic gates
A major challenge in collaborative filtering methods is how to produce recommendations for
cold items (items with no ratings), or integrate cold items into an existing catalog. Over the …
cold items (items with no ratings), or integrate cold items into an existing catalog. Over the …
Model-driven approach running route two-level SVD with context information and feature entities in recommender system
KV Rodpysh, SJ Mirabedini, T Banirostam - Computer Standards & …, 2022 - Elsevier
In digital businesses, the offers of goods and services to users in recommendation systems
are generally based on the features of the items and the demands of the users …
are generally based on the features of the items and the demands of the users …
Switching hybrid for cold-starting context-aware recommender systems
Finding effective solutions for cold-starting Context-Aware Recommender Systems (CARSs)
is important because usually low quality recommendations are produced for users, items or …
is important because usually low quality recommendations are produced for users, items or …
Addressing cold start challenges in recommender systems: towards a new hybrid approach
Along with the rapid expansion of data in information systems, managing and searching for
personalized information has become a tedious task. Users are overwhelmed by a wide …
personalized information has become a tedious task. Users are overwhelmed by a wide …
A new hybrid-enhanced recommender system for mitigating cold start issues
With the significant expanding flows of data circulating on the Internet, users are
overwhelmed by an era of information explosion. Hence, Recommender Systems have …
overwhelmed by an era of information explosion. Hence, Recommender Systems have …
Developing multi-task recommendations with long-term rewards via policy distilled reinforcement learning
With the explosive growth of online products and content, recommendation techniques have
been considered as an effective tool to overcome information overload, improve user …
been considered as an effective tool to overcome information overload, improve user …
Preference mining using neighborhood rough set model on two universes
K Zeng - Computational Intelligence and Neuroscience, 2016 - Wiley Online Library
Preference mining plays an important role in e‐commerce and video websites for enhancing
user satisfaction and loyalty. Some classical methods are not available for the cold‐start …
user satisfaction and loyalty. Some classical methods are not available for the cold‐start …