The 3rd International Workshop on News Recommendation and Analytics (INRA 2015) is held in conjunction with RecSys 2015 Conference in Vienna, Austria. This paper presents a brief summary of the INRA 2015. This workshop aims to create an interdisciplinary community that addresses design issues in news recommender systems and news analytics, and promote fruitful collaboration opportunities between researchers, media companies and practitioners. We have a keynote speaker and an invited demo presentation in addition to 4 papers accepted in this workshop.
H.0 [Information Systems]: General Recommender systems; news recommendation; analytics
The motivation for news recommender systems is the tremendous amount of news articles available online and the dynamic nature of news domain. For a user it is getting harder to reach the relevant news items according to her personal interests and preferences. News recommender systems aim to bring the most relevant news items to the users.
Each domain in recommender systems has di erent characteristics and requires di erent approaches to make successful recommendations. Compared to other recommender system domains like books, music and movies, news recommender systems have particular challenges which requires a deeper analysis of both the user, content and their relationships. The news domain is characterized by a constant ow of unstructured, fragmentary, and unreliable news stories from numerous sources and di erent perspectives. Some important challenges of news domain are:
Dynamic environment: Every hour hundreds of new articles is published by di erent sources, Faster changing user interests compared to other domains. User interests in movies, music or books change much slower than news, Willingness to read news articles that are independent from user interests like breaking news, Recency issues of news articles (people tend to read recent news, not the old ones), Unstructured subjective content that create content analysis problems and may turn recommendations unreliable.
This workshop addresses primarily news recommender systems and news analytics, with a particular focus on user proling and techniques for dealing with and extracting knowledge from large-scale news streams. The news streams may originate in large media companies, but may also come from social sites, where user models are needed to decide how user-generated content is to be taken into account. As part of news recommendation and analytics, Big Data architectures and large-scale statistical and linguistic techniques are used to extract aggregated knowledge from large news streams and prepare for personalized access to news. 2.
News summarization, classi cation and sentiment analysis, Recommender systems and news personalization,
In INRA 2015 we have received 6 submissions, of which 4 were accepted for presentation. The submissions to our workshop includes good quality of works for user pro ling, social network analysis, hybrid methods and deep learning for news recommendation. This year we have the acceptance rate of 66%. In INRA 2015 we have a keynote speaker who has a very good background of industrial and academic work on data analytics and news research. INRA also includes a demo session with a full- edged news recommender system that has been developed as part of the SmartMedia program at NTNU in Trondheim. This system integrates numerous Norwegian news sources and demonstrates how the use of context can improve the quality of personalized mobile news aggregators. 3.1
Dr. Bahareh Heravi is the keynote speaker of INRA 2015. She is a Research Fellow at Insight Centre for Data Analytics @ NUI Galway and the founder and Leader of the Insight News Lab 1 (Digital Humanities and Journalism). She is an Adjunct Lecturer and a programme board member of Journalism Studies at the National University of Ireland, Galway. Dr Heravi's research and teaching are at the nexus of data, technology and journalism. She has worked with and within various news organizations. Her main research interests are in the areas of Data and Computational Journalism, Information Science, Social Media & Citizen Sensing, Semantic Web and Linked Data. She leads a number of projects at the Insight News Lab, including RTE News360, Newswire 2.0, VeritaWire, Social Semantic Journalism and the Social Repository of Ireland. Dr Heravi is the founder of Irish Times Data 2 and also the founder and organizer of Hacks/Hackers Dublin. She is the former Lead Data Scientist at The Irish Times, where she lead the Irish Times'R&D programme and pioneered data innovation in the newsroom. Dr. Heravi's talk is about data journalism as a practice, the new directions and challenges in news organizations. 3.2
3rd International Workshop on News Recommendation and Analytics (INRA 2015) is based on the following previous workshops: International News Recommender Systems Workshop and Challenge (NRS)3 held in conjunction with the 7th ACM Recommender Systems Conference in 2013. This workshop had a very limited scope, which restricted the number of submissions and led to an acceptance rate of 75%.
International Workshop on News Recommendation and Analytics (NRA) 2014 4 held in conjunction with 22nd Conference on User Modelling, Adaptation and Personalization (UMAP) in 2014. The workshop scope was extended with news analytics, which is closely lined with the eld of news recommendation. The acceptance rate was 50%. 4. 4.1
Jon Atle Gulla, Professor at Department of Computer and Information Science, Norwegian University of Science and Technology (NTNU), Norway 4.2
4.3
Na seh Shabib, Norwegian University of Science and Technology (NTNU), Department of Computer and Information Science, Norway
Jon Espen Ingvaldsen, Norwegian University of Science and Technology (NTNU), Department of Computer and Information Science, Norway