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Modeling Multi-interest News Sequence for News Recommendation
In MINS, a news encoder based on self-attention is devised on learn an informative embedding for each piece of news, and then a novel parallel interest network is devised to extract the potential multiple interests embedded in the news sequence in preparation for the subsequent next-news recommendations.
Aspect-driven User Preference and News Representation Learning for News Recommendation
News recommender systems are essential for helping users to efficiently and effectively find out those interesting news from a large amount of news.
Cell A* for Navigation of Unmanned Aerial Vehicles in Partially-known Environments
Proper path planning is the first step of robust and efficient autonomous navigation for mobile robots.
Robotics Systems and Control Systems and Control
