Deep learning based recommender system using cross convolutional filters
With the recent development of online transactions, recommender systems have
increasingly attracted attention in various domains. The recommender system supports the …
increasingly attracted attention in various domains. The recommender system supports the …
Matching algorithms: Fundamentals, applications and challenges
Matching plays a vital role in the rational allocation of resources in many areas, ranging from
market operation to people's daily lives. In economics, the term matching theory is coined for …
market operation to people's daily lives. In economics, the term matching theory is coined for …
SARWAS: Deep ensemble learning techniques for sentiment based recommendation system
Identifying user preferences is a complex operation, which makes its automa-tion
challenging, and existing recommendation systems that rely on one of the parameters …
challenging, and existing recommendation systems that rely on one of the parameters …
A hybrid recommender system for recommending smartphones to prospective customers
PK Biswas, S Liu - Expert Systems with Applications, 2022 - Elsevier
Recommender Systems are a subclass of machine learning systems that employ
sophisticated information filtering strategies to reduce the search time and suggest the most …
sophisticated information filtering strategies to reduce the search time and suggest the most …
Multi-interest diversification for end-to-end sequential recommendation
Sequential recommenders capture dynamic aspects of users' interests by modeling
sequential behavior. Previous studies on sequential recommendations mostly aim to identify …
sequential behavior. Previous studies on sequential recommendations mostly aim to identify …
Improving end-to-end sequential recommendations with intent-aware diversification
Sequential recommenders that capture users' dynamic intents by modeling sequential
behavior, are able to accurately recommend items to users. Previous studies on sequential …
behavior, are able to accurately recommend items to users. Previous studies on sequential …
CNNRec: Convolutional Neural Network based recommender systems-A survey
Easy internet access and technological advancements have resulted in information overload
and a plethora of options, making decision-making extremely difficult. Recommender …
and a plethora of options, making decision-making extremely difficult. Recommender …
IR-Rec: An interpretive rules-guided recommendation over knowledge graph
J Chen, J Yu, W Lu, Y Qian, P Li - Information Sciences, 2021 - Elsevier
Most existing recommendation methods focus on the improvement of recommender
accuracy while ignoring the influence of recommended explanation. Recommender …
accuracy while ignoring the influence of recommended explanation. Recommender …
A federated deep learning framework for privacy-preserving consumer electronics recommendations
Recommender systems (RSs) have proven to be highly effective in guiding consumers
towards well-informed purchase decisions for electronics. These systems can provide …
towards well-informed purchase decisions for electronics. These systems can provide …
Design and comparative analysis of new personalized recommender algorithms with specific features for large scale datasets
S Bhaskaran, R Marappan, B Santhi - Mathematics, 2020 - mdpi.com
Nowadays, because of the tremendous amount of information that humans and machines
produce every day, it has become increasingly hard to choose the more relevant content …
produce every day, it has become increasingly hard to choose the more relevant content …