News publishers have decreased disseminating news through conventional newspapers
and have migrated to the use of digital means like websites and purpose-built mobile …

More and more people read the news online, eg, by visiting the websites of their favorite
newspapers or by navigating the sites of news aggregators. However, the abundance of …

Modeling user's long-term and short-term interests is crucial for accurate recommendation.
However, since there is no manually annotated label for user interests, existing approaches …

Personalized news recommendation is important for users to find interesting news
information and alleviate information overload. Although it has been extensively studied …

User profiling is an important step for solving the problem of personalized news
recommendation. Traditional user profiling techniques often construct profiles of users …

Recommender systems aim to get the relevant data, based on the user's interests. One of
the key problems of the recommender systems is to maintain the dataset and to retrieve the …

Personalized news recommender systems have gained increasing attention in recent years.
Within a news reading community, the implicit correlations among news readers, news …

Recommender systems have been developed to overcome the information overload
problem by retrieving the most relevant resources. Constructing an appropriate model to …

Personalized news recommendation aims to help users find news content they prefer, which
has attracted increasing attention recently. There are two core issues in news …

The task of designing a recommender system is a complex process. Because of the many
technological advancements that may be included in a recommender system, engineers are …