The CLEF NewsREEL challenge allows researchers to evaluate news recommendation algorithms both online (NewsREEL Live) and offline (News- REEL Replay). Compared with the previous year NewsREEL challenged participants with a higher volume of messages and new news portals. In the 2017 edition of the CLEF NewsREEL challenge a wide variety of new approaches have been implemented ranging from the use of existing machine learning frameworks, to ensemble methods to the use of deep neural networks. This paper gives an overview over the implemented approaches and discusses the evaluation results. In addition, the main results of Living Lab and the Replay task are explained
News recommender systems provide users with access to news stories that they find interesting and re...
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item ...
News recommender systems provide users with access to news stories that they find interesting and re...
The CLEF NewsREEL challenge allows researchers to evaluate news recommendation algorithms both onlin...
Running in its third year at CLEF, NewsREEL challenged participants to develop news recommendation ...
Running in its third year at CLEF, NewsREEL challenged participants to develop news recommendation ...
The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to evaluate and...
This paper summarises objectives, organisation, and results of the first news recommendation evalua...
News recommender systems provide users with access to news stories that they find interesting and re...
Providing high-quality news recommendations is a challenging task because the set of potentially rel...
News reader struggle as they face ever increasing numbers of articles. Digital news portals are bec...
This paper summarises objectives, organisation, and results of the first news recommendation evaluat...
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item...
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item...
News reader struggle as they face ever increasing numbers of articles. Digital news portals are bec...
News recommender systems provide users with access to news stories that they find interesting and re...
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item ...
News recommender systems provide users with access to news stories that they find interesting and re...
The CLEF NewsREEL challenge allows researchers to evaluate news recommendation algorithms both onlin...
Running in its third year at CLEF, NewsREEL challenged participants to develop news recommendation ...
Running in its third year at CLEF, NewsREEL challenged participants to develop news recommendation ...
The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to evaluate and...
This paper summarises objectives, organisation, and results of the first news recommendation evalua...
News recommender systems provide users with access to news stories that they find interesting and re...
Providing high-quality news recommendations is a challenging task because the set of potentially rel...
News reader struggle as they face ever increasing numbers of articles. Digital news portals are bec...
This paper summarises objectives, organisation, and results of the first news recommendation evaluat...
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item...
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item...
News reader struggle as they face ever increasing numbers of articles. Digital news portals are bec...
News recommender systems provide users with access to news stories that they find interesting and re...
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item ...
News recommender systems provide users with access to news stories that they find interesting and re...