English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Interactive video and TV content has become available in many settings which include the web, mobile devices, and desktop applications, as well as smart TVs. Although the above multimedia developments (e.g., Web-based TV, IPTV, and broadcast TV) have followed parallel or even competing paths, there is a set of underlying common themes that regard the users, as creators, distributors, and viewers of content. In the past, broadcast developments have been in competition with video streaming approaches, and the TV as device has been in conflict with the PC. Nevertheless, the convergence of network and rendering platforms has made such distinctions somewhat superficial. In particular, there are significant research issues that regard the social and the personal preferences of the user. Thus, the recommendation and delivery of multimedia content requires attention to significant research issues, such as semantics, pragmatics, and user preferences. The main goals of this special issue is to assess current approaches, systems, and applications, to evaluate how they treat the main issues of recommending and delivering video and TV content, as well as to propose novel designs for future multimedia systems. This special issue had both direct submissions to our call for papers as well as submissions of papers presented at the 9th European Interactive TV and Video conference (EuroiTV’11), held in Lisbon, Portugal from June 29 to July 1 2011. These conference papers have been significantly extended from their conference originals through more indepth literature reviews and further results and analysis. From this pool and after thorough peer reviewing, we have included six papers in this issue, two of which came from extended versions of EuroiTV’11 conference papers and the other four from direct submissions. In this special issue, Kyoko Ariyasu, Hiroshi Fujisawa and Shyunji Sunasaki present the design and field trial evaluation of their system that leverages Twitter messages to drive recommendation services. The algorithms rely on auxiliary programme information and the time series of Twitter messages along with their similarity as input. The system achieves correct topic extraction rates of 85 % for messages with matching entries in programme metadata, 65 % for messages with matches in the closed-caption data of a programme, and has a 66 % correct sentiment classification of messages. Faustino Angel Sanchez, Marta Barrilero, Federico Alvarez, and Guillermo Cisneros describe their TV recommender systems, which models user interest in content from consumption data. The system uses hidden Markov models and Bayesian inference to compute user interest in real time and its recommendation, which were very satisfactory after a week of use and have been verified through questionnaires. It improves over previous research by the introduction of connected items and a notion of global interest, which takes into consideration the changes in users’ taste tendencies. Heung-Nam Kim, Mark Bloess and Abdulmotaleb El Saddik propose Folkommender, a recommender system G. Lekakos (&) Department of Management Science and Technology, Athens University of Economics and Business, Athens, Greece e-mail: glekakos@aueb.gr

Special Issue on Social Recommendation and Delivery Systems for Video and TV Content