2018, Article in monograph or in proceedings (The 2nd fatrec workshop on responsible recommendation)Personalization of media services is gaining more and more traction, e.g., through the rise of personalization driven by recommender systems across media outlets. At the same time, we see a general rise in distrust and skepticism around the collection and processing of personal data, spurred by policy changes such as the introduc- tion of the GDPR, data breach incidents, and the rise of privacy concerns in general. We feel it is of central importance to be trans- parent about the information we collect, and the ways we use it. In this position paper we motivate the importance of enabling transparency through explaining our recommender system. More specifically, we aim to explain the inferred user profiles that are cen- tral to content-based recommender systems. We describe how user profile explanations can contribute to, or enable different aspects of our recommender system; transparency to help users better under- stand the inner workings of the recommender system, scrutability to allow users to provide explicit feedback on the internally con- structed user profiles, and self-actualization to support users in understanding and exploring their personal preferences. Finally, we believe that user profile explanations can find novel and interesting explanations as an end in itself.
2018, Article in monograph or in proceedings (The algorithmic personalization and news (apen18) workshop at icwsm '18)FD Mediagroep (FDMG1 ) is the leading information provider in the financial economic domain in the Netherlands. FDMG operates “Het Financieele Dagblad” (FD) a daily finan- cial newspaper, similar to the Financial Times. In addition, FDMG operates the daily all-news radio station “Business News Radio” (BNR). As we have a wide variety of users with various backgrounds and interests, we believe that digital me- dia (both news articles and radio) should be personalized to match the interests of a particular customer. We are therefore working on personalization of FDMG’s digital media:
• Personalized news: Recommendations and personalized summaries of news articles that match the reading pref- erences and interests of our readers
• Personalized radio: A non-linear radio experience with ra- dio snippets that match the listener’s interests
In both personalized news and personalized radio we are looking not only at introducing recommender systems but also at personalized ways to present the information using automated summarization (news) and audio segmentation (ra- dio) methods
2018, Article in monograph or in proceedings (The 17th dutch-belgian information retrieval workshop)In this demonstration paper we describe the SMART Radio app
1
forBNRNieuwsradio. TheSMARTRadioappisanextensionto
the current BNR app, which offers users a more personalized news radio experience. It does so by automatically fragmenting shows to offer our users more targeted and focused fragments of audio, not full shows. We employ audio segmentation and audio topic- tagging techniques to achieve this, which we describe in this paper. In its present form, users can subscribe to tags to get appropriate suggestions of relevant radio fragments. In the future we would like to improve the app’s personalization, by using information of the user’s interaction with the app.