The emergence of content- and context-aware search engines, which not only personalize searching and delivery but also the content, has caused the emergence of new infrastructures capable of end-to-end ubiquitous transmission of personalized multimedia content to any device on any network at any time. Personalizing and adapting content requires processing of content and recognizing patterns in usersβ behaviour on the other. Personalizing and adapting the semantic content of multimedia enables applications to make just-in-time intelligent decisions regarding this content, which in turn makes interaction with the multimedia content an individual and individually rewarding experience. Highlighting the changing nature of the field, Advances in Semantic Media Adaptation and Personalization, Volume Two discusses the state of the art, recent advances, and future outlooks for semantic media adaptation and personalization. Topics include: Collaborative Content Modeling Automatic Content Feature Extraction to Content Models Semantic Languages for Content Description Video Content Adaptation Adaptive Video Content Retrieval Content Similarity Detection Personalized Content Podcasting Adaptive Web Interaction As content and service providers recognize the value of new services and new markets, they will invest in technologies that adapt and personalize content. Industry, in response, has released new standards such as MPEG-7, MPEG21, and VC-1 that enable propagation of semantic media, adaptation, and personalization. Consequently, a broad range of applications are emerging across many industry sectors, such as music, film, games, television, and sports. Bringing together insight from researchers and practitioners, this book provides a sampling of the latest thinking in the field.