Online news services such as Microsoft News which collect news from various sources and display them to users in a unified view have gained huge popularity for online news reading. However, massive news articles emerge every day, and it is overwhelming for users to read all news to find their interested content. Thus, news recommendation and intelligence techniques are critical for online news platforms to help users find interested news, improve their reading experiences and alleviate information overload.
News recommendation and intelligence are of significant relevance to the NLP community. News articles usually contain rich textual information such as title and body. It is very important for news related applications to understand news content from their texts using NLP techniques. In addition, news articles on news websites emerge and update very quickly. Many new articles are posted continuously, and existing news articles will disappear after a short period of time. Thus, there is a severe cold-start problem in news recommendation and intelligence scenarios, and understanding news by their content is necessary. Besides, there is usually no explicit feedback such as ratings provided by users of online news platforms, and we usually need to model users’ interests from their implicit feedback like browsing and click behaviors. However, user interests are usually diverse and evolutional, which are difficult to be accurately modeled. Thus, further researches from both NLP and data mining communities are highly needed to tackle the various challenges in news recommendation and intelligence.
The purpose of this workshop is to call for research and practice on news recommendation and intelligence to promote the techniques in these fields. It welcomes research works that study news recommendation and intelligence in various aspects, including but not limited to novel algorithms, data analysis, real-world systems/applications, and ethical problems like fairness, diversity and user privacy. In addition, this workshop will hold a new iteration of the MIND news recommendation competition, which can be served as a good testbed for news recommendation research. We hope this workshop can help attendees master a better understanding of news recommendation and intelligence, facilitate future research in these fields, and provide useful insights for other related NLP fields.
December 21st, 2020
November 27th, 2020
October 2nd, 2020
|Submission site opens||Friday||December 18, 2020|
|Paper submissions due||Monday||
January 25, 2021
|Notification of acceptance||Monday||
February 15, 2021
|Camera-ready papers due||Sunday||February 28, 2021|
All deadlines are 11.59 pm UTC -12h.