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Interactive Recommendation Systems
Recommendation systems have become an indispensable part of many online platforms such as online shops or social media, designed to facilitate users’...
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Voting Classifier-Based Crop Recommendation
The three most important necessities for human life are food, shelter, and clothing. Young people who are technologically savvy have witnessed a...
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A Survey of Personalized News Recommendation
Personalized news recommendation is an important technology to help users obtain news information they are interested in and alleviate information...
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Ripple Knowledge Graph Convolutional Networks for Recommendation Systems
Using knowledge graphs to assist deep learning models in making recommendation decisions has recently been proven to effectively improve the model’s...
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MMusic: a hierarchical multi-information fusion method for deep music recommendation
With the explosive growth of music volume, music recommendation systems have become an important tool for online music platforms to alleviate the...
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Graph-based dynamic attribute clip** for conversational recommendation
Conversational recommender systems (CRS) enable traditional recommender systems to interact with users by asking questions about their preferences...
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Context-Aware Interactive Knowledge-Based Recommendation
Recommender systems have widely been used in the past few years as a recipe to success in e-commerce. Already, 35 percent of what consumers purchase...
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Personality-based and trust-aware products recommendation in social networks
In recent years, with the development of technology, the shop** approach of people has moved towards pervasive online social shop**. As a result,...
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KLECA: knowledge-level-evolution and category-aware personalized knowledge recommendation
Knowledge recommendation plays a crucial role in online learning platforms. It aims to optimize the service quality so as to improve users’ learning...
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Knowledge graph for recommendation system: enhanced relation reliability and prediction probability (ERRaPP)
With the current explosion of information, the end-users find it challenging to filter this information. Recommendation systems present solutions to...
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Group-to-group recommendation with neural graph matching
Nowadays, with the development of recommender systems, an emerging recommendation scenario called group-to-group recommendation has played a vital...
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Representation learning: serial-autoencoder for personalized recommendation
Nowadays, the personalized recommendation has become a research hotspot for addressing information overload. Despite this, generating effective...
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Multimodal Interactive Network for Sequential Recommendation
Building an effective sequential recommendation system is still a challenging task due to limited interactions among users and items. Recent work has...
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An Ensemble Model for Combining Deep Matrix Factorization and Image-Based Recommendation Systems
Recommender systems are widely used in many domains, especially in E-commerce. It can be used for attracting users by recommending appropriate...
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DCLGM: Fusion Recommendation Model Based on LightGBM and Deep Learning
The recommendation system can mine valuable information according to user preferences, so it is widely used in various industries. However, the...
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Graph neural news recommendation based on multi-view representation learning
Accurate news representation is of crucial importance in personalized news recommendation. Most of existing news recommendation model lack...
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Uncertainty-aware graph neural network for semi-supervised diversified recommendation
Graphs are a powerful tool for representing structured and relational data in various domains, including social networks, knowledge graphs, and...
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A Personalized Course Recommendation Model Integrating Multi-granularity Sessions and Multi-type Interests
The open online course (MOOC) platform has seen an increase in usage, and there are a growing number of courses accessible for people to select. An...
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Hamiltonian deep neural network fostered sentiment analysis approach on product reviews
In recent times, online shop** has become commonly used method for consumers to make purchases and engage in consumption with the rapid advancement...
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Multi-behavior recommendation based on intent learning
Users often exhibit different intents when interacting with recommender systems, guiding their engagement across various behavior categories like...
