About

Nowadays wired and wireless broadband infrastructures facilitate seamless user access to interactive TV and media content through various means, like the Web, mobile network, and smart TV. Several technologies, like Web-based TV, IPTV, and Broadcast TV, have emerged and followed parallel development paths, and they all followed the paradigm of considering the users to be the distributors, consumers, and sometimes even the suppliers of the media content. In this setting, each user contributes to the delivery of content in a complex and heterogeneous environment consisting of diverse platforms (wired, wireless, mobile, fixed, ad-hoc), devices (TV, smartphone, PC, tablet, public display), and users (preferences, interests, needs, demographic characteristics).

This cross-platform convergence of TV, media, and the Web has revolutionized the established TV and media content consumption practices. In addition to the pure viewing functionalities like skipping, repeating, or recording content, it allows users to access additional information about the media content, virtually socialize with other users, select their desired content to consume and determine its delivery mode, express their experiences and feelings, and affect other users. This, however, raises numerous challenges related to user modeling and personalization, and brings to the fore research questions related to user interaction, social media, and content delivery. For example, users influence each other through the exchange of ratings and comments about the consumed media content, they are connected 24x7 through a variety of devices and many networks, they leave identifiable traces that can be used to profile them, and they interact with other information, devices, and users while consuming the media content. The workshop will center on these and other questions related to user modeling and personalization for interactive TV and media content consumption.

Objectives

The workshop has two key objectives. Firstly, we aim to provide a venue for the presentation of the latest approaches, systems, and applications focused in the area of TV and media content consumption personalization. Secondly, we intend to structure the workshop in a way that will facilitate direct interaction, sharing of research findings, and establishment of collaborations. More specifically, the workshop aims to:

1. Provide the venue to report the latest research findings and advancements in the area of interactive TV and media content personalization.
2. Foster interaction and exchange of ideas within the TV and media content personalization research community.
3. Provide an opportunity for information exchange and possible future research collaboration within the community
4. Re-visit the research agenda in the area of TV and media content personalization in the light of recent developments in the Social Web, Semantic Web, and Mobile/Ubiquitous Computing research.

Scope

The scope of the workshop includes (but is not limited to) the following topics around TV, video, and media content personalization:

• User modeling from user-content interactions
• Personalization and user-based adaptation
• Intelligent filtering and search
• Personalized content delivery
• Adaptive recommendations
• Cold-start problem in media personalization
• Group- and family-based recommendations
• Context-aware recommendations
• Automatic content annotation
• Media content consumption and social networks
• Use of ubiquitous and mobile devices
• Intelligent interfaces for media content
• Privacy and ethical issues
• Crowd-sourcing on media content
• Viral content distribution
• Architectures and platforms
• Applications in various domains such as entertainment, advertisement, e-commerce, and e-health

Accepted papers

1. Mengxi Xu, Shlomo Berkovsky, Irena Koprinska, Sebastien Ardon and Kalina Yacef
   Time-Dependent Clustering of TV Viewers


2. Dávid Zibriczky, Balázs Hidasi, Zoltán Petres and Domonkos Tikk
   Personalized recommendation of linear content on interactive TV platforms: beating the cold start and noisy implicit user feedback


3. Stylianos Asteriadis, Kostas Karpouzis, Noor Shaker and Georgios N. Yannakakis
   Does your profile say it all? Using demographics to predict expressive head movement during gameplay


4. John Champaign and Robin Cohen
   Personalized presentation of multimedia objects for home healthcare environments: a peer-based intelligent tutoring approach