Monthly Archives: March 2012

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NoTube at MIPTV2012

Lora Aroyo will present NoTube at MIPTV2012 as part of the MIPCube innovation lab for future of TV: Friday 30 March 2012, 10:40 AM to 11:20 AM, INNOVATION ALLEY DEMOS #1_CONTENT DISCOVERY – SOCIAL APPS, USER INTERFACES… (Location: Gare Maritime, Innovation Agora) Saturday 31 March 2012, 14:50 PM to … Continue reading

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NoTube exploits the richness of data on the Web to enhance the TV experience (video)

This video summarizes the NoTube approach to open source software that allows you to exploit the richness of data on the Web to enhance the TV experience. We analyze social web user activities to create continuously evolving user profiles. We … Continue reading

Posted in About Notube, Beancounter, Demonstration Videos, Linked Data, News, Recommendations, Second screens, Social TV, Web-connected TV | Tagged , , , | Leave a comment

Paper on NoTube’s HBB Scenarios

Following the investigations about the common ground of NoTube and HbbTV we did last year (see our blog post), we concluded this activity with a White Paper contributing our experiences and visions to future specifications of HbbTV and, of course, also … Continue reading

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Results from Loudness Web Evaluation now online

In December 2011, we already published preliminary results of the User Evaluation on Loudness Harmonisation on the Web in this blog. At the same time, we called for more participation to increase the data set for the final analysis. By … Continue reading

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Beancounter user research part 2: Reactions to the Beancounter user interface

Last week I wrote about our findings concerning people’s attitudes towards privacy and sharing of the types of personal data that the Beancounter (NoTube’s user profiling service) can collect. This blog post is going to focus on some early reactions … Continue reading

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Beancounter user research part 1: creating social experiences, sharing, privacy, and user control of personal data

NoTube’s Beancounter software is a user-profiling service that implicitly determines a person’s most up-to-date interests based on an aggregation of their existing activities on the Social Web. This profile can then be used as input for personalised TV recommendations. During … Continue reading

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