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Improving selection diversity using hybrid graph-based news recommenders
With the ever-growing amount of news, there is an increasing need for tools capable of filtering out and tailoring the content to the wants and needs...
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Candidate-Aware Dynamic Representation for News Recommendation
With the application of collaborative filtering and deep neural network in news recommendation, it becomes more feasible and easier to capture users’...
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MM-Locate-News: Multimodal Focus Location Estimation in News
The consumption of news has changed significantly as the Web has become the most influential medium for information. To analyze and contextualize the...
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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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Say No2Ads: Automatic Advertisement and Music Filtering from Broadcast News Content
The incredible growth in available news content has been met with steeply increasing demand for news amongst the general population. The 24/7 news...
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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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Fake News Detection Using Transfer Learning
In this innovative study, multi-task transfer study and Natural Language Processing or NLP join forces to fight the ever-growing challenge of...
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Fake News Detection Using Hybrid Deep Learning Method
The growth of online social networks platforms in recent years has resulted in the widespread dissemination of social news such as commercial...
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The impacts of relevance of recommendations and goal commitment on user experience in news recommender design
Cold start and data sparsity are problems hindering the function of news recommender systems. Optimally serving first-time users through relevant...
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TBNF:A Transformer-based Noise Filtering Method for Chinese Long-form Text Matching
In the field of deep matching, a large amount of noisy data in Chinese long texts affects the matching effect. Most long-form text matching models...
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An integrated topic modeling and auto-encoder for semantic-rich network embedding and news recommendation
In recent years, network representation learning is considered as a crucial research direction which explicitly supports multiple problems in...
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A comprehensive overview of fake news detection on social networks
As social media and web-based forums have grown in popularity, the fast-spreading trend of fake news has become a major threat to the government and...
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SSLE: A framework for evaluating the “Filter Bubble” effect on the news aggregator and recommenders
Recommendation algorithms are data filtering tools that make use of algorithms and data to recommend the most relevant items to a particular user....
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Fake News Detection Using Machine Learning
The news which is specially created to misguide as well as mislead the readers is termed fake news. Fake news can cause potential harm to both the...
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FairCF: fairness-aware collaborative filtering
Collaborative filtering (CF) techniques learn user and item embeddings from user-item interaction behaviors, and are commonly used in recommendation...
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Fake News Detection in Dravidian Languages Using Transformer Models
Nowadays, fake news is spreading rapidly. Many resources are available for fake news detection in high-resource languages like English. Due to the...
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Detecting fake news for COVID-19 using deep learning: a review
The December of 2019, marked the start of one of the biggest pandemics that the human race had seen for some centuries. COVID-19 after originating...
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Bangla News Classification Employing Deep Learning
In this paper, we have introduced a deep learning model for the classification of Bangla news articles as it is an important task for maintaining and...
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Twittener: Improving News Experience with Sentiment Analysis and Trend Recommendation
The Internet provides a profusion of online sources for both trending topics and news. With the vast content made available, it might risk readers in...
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ZS-CEBE: leveraging zero-shot cross and bi-encoder architecture for cold-start news recommendation
News recommendation systems heavily rely on the information exchange between news articles and users to personalize the recommendation. Consequently,...
