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Neural Network Approaches for Recommender Systems
AbstractRecommender systems are special algorithms that allow users to receive personalized recommendations on topics that interest them. Systems of...
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Privacy protection in cross-platform recommender systems: techniques and challenges
This paper provides an in-depth exploration of privacy protection in crossplatform recommender systems. With the rapid development of information...
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Health Recommender Systems
According to experts, lifestyle disorders pose a severe threat to human civilization. These illnesses cause a progressive deterioration of health...
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Group Recommender Systems An Introduction
This book discusses different aspects of group recommender systems, which are systems that help to identify recommendations for groups instead of...
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Evaluating Group Recommender Systems
In the previous chapters, we have learned how to design group recommender systems but did not explicitly discuss how to evaluate them. The evaluation...
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Assimilation and Contrast: The Two-sided Anchoring Effects of Recommender Systems
Previous studies on the behavioral implications of recommender systems suggest that consumer preferences after consumption are malleable and tend to...
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An improved restricted Boltzmann Machine using Bayesian Optimization for Recommender Systems
Several web services comprise a Recommender System (RS) that assists the user to discover new products and services such as movies, books, articles,...
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Which Data Quality Model for Recommender Systems?
Although data quality has been acknowledged as a significant issue in a variety of information systems research studies, it has received little...
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An integration method for optimizing the use of explicit and implicit feedback in recommender systems
The recent changes in consumption patterns and the development of the Internet have increased the diversity of user feedback in the recommender...
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Multi-source information contrastive learning collaborative augmented conversational recommender systems
Conversational Recommender Systems (CRS) aim to provide high-quality items to users in fewer conversation rounds using natural language. Despite...
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Toward Recommender Systems Scalability and Efficacy
Recommender systems play a key role in many branches of the digital economy. Their primary function is to select the most relevant services or...
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Significant Factors for Recommender Systems Using Sentimental Analysis
In this paper, recommender systems (RS) are examined to make numerous improvements in recommendations based on Sentiment Analysis (Asani et al. Mach...
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Latent Semantic Indexing-Based Hybrid Collaborative Filtering for Recommender Systems
Advances in information technologies increase the number and diversity of digital objects. This increase poses significant problems in reaching the...
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Fully adaptive recommendation paradigm: top-enhanced recommender distillation for intelligent education systems
Top-N recommendation has received great attention in assisting students in providing personalized learning guidance on the required subject/domain....
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An efficient privacy-preserving recommender system in wireless networks
Recommender systems have been widely used for implementing personalised content on many mobile online services to reduce computational overload and...
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A General Matrix Factorization Framework for Recommender Systems in Multi-access Edge Computing Network
Due to the growing number of users and items in recommender system, along with the more complex algorithms for precise recommendation, recommender...
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Social Recommender Systems in E-Learning Environments: A Literature Review
Since the beginning of the COVID-19 pandemic, e-learning platforms have received a lot of attention as a way to acquire knowledge remotely. These...
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Analysis of Deep Learning Methods Used in Tourism Recommender Systems
Recommender systems are widely used users’ lives easier by assisting them in narrowing down their product of choice from the various alternatives....
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Object-aware Policy Network in Deep Recommender Systems
Deep learning has been successfully applied in the recommender system. Low-dimensional dense embedding is typically used to represent the feature of...
