The advent of large language models marks a revolutionary breakthrough in artificial
intelligence. With the unprecedented scale of training and model parameters, the capability …

Recommender systems (RSs) have been playing an increasingly important role for informed
consumption, services, and decision-making in the overloaded information era and digitized …

摘要深度学习是机器学习领域一个重要研究方向, 近年来在图像处理, 自然语言理解,
语音识别和在线广告等领域取得了突破性进展. 将深度学习融入推荐系统中 …

Click-through rate (CTR) prediction, whose goal is to estimate the probability of a user
clicking on the item, has become one of the core tasks in the advertising system. For CTR …

“Any AI smart enough to pass a Turing test is smart enough to know to fail it.”–*** Ian
McDonald Neural networks were developed to simulate the human nervous system for …

Top-N sequential recommendation models each user as a sequence of items interacted in
the past and aims to predict top-N ranked items that a user will likely interact in a» near …

With the growing volume of online information, recommender systems have been an
effective strategy to overcome information overload. The utility of recommender systems …

Recommender systems are one of the most successful applications of data mining and
machine-learning technology in practice. Academic research in the field is historically often …

Nowadays, more and more news readers read news online where they have access to
millions of news articles from multiple sources. In order to help users find the right and …

Deep learning methods have led to substantial progress in various application fields of AI,
and in recent years a number of proposals were made to improve recommender systems …