• Introduction of the Autonomous Content Entity (ACE) concept combining content, metadata, intelligence in a single entity
• Knowledge and context-assisted content analysis techniques based on a multimedia ontology infrastructure to support semantic entity detection and tracking of ACE content
• High-level semantic reasoning tools for automatic annotation and generation of the ACE metadata layer
• Query analysis tools and intelligent ACE search, retrieval, ranking and relevance feedback mechanisms
• Intelligent mechanisms to manage ACE communication, and methods to produce aesthetically appealing content and enhanced visualisation for navigation and rendering
• User interfaces and adaptivity support for aceMedia target application

MESH: Multimedia Semantic Syndication for Enhanced News Services, 6th FP IST Integrated Project, 2006-2008.

Multimedia Semantic Syndication for Enhanced News Services (MESH) will apply multimedia analysis and reasoning tools, network agents and content management techniques to extract, compare and combine meaning from multiple multimedia sources, and produce advanced personalized multimedia summaries, deeply linked among them and to the original sources to provide end users with an easy-to-use 'multimedia mesh' concept, with enhanced navigation aids. A step further will empower users with the means to reuse available content by offering media enrichment and semantic mixing of both personal and network content, as well as automatic creation from semantic descriptions. Encompassing all the system, dynamic usage management will be included to facilitate agreement between content chain players (content providers, service providers and users). In a sentence, the project will create multimedia content brokers acting on behalf of users to acquire, process, create and present multimedia information personalized (to user) and adapted (to usage environment). These functions will be fully exhibited in the application area of news, by creation of a platform that will unify news organizations through the online retrieval, editing, authoring and publishing of news items.

K-Space: Knowledge Space of Semantic Inference for Automatic Annotation and Retrieval of Multimedia Content, 6th FP IST NoE, 2006-2008.

K-Space will create a sustainable network of world-leading research teams from academia and industry to conduct integrative research and dissemination activities in semantic inference for automatic and semi-automatic annotation and retrieval of multimedia content, aiming at closing the gap between the low-level content descriptions that can be computed automatically by a machine and the richness and subjectivity of semantics in high-level human interpretations of audiovisual media. Specifically, K-Space integrative research will focus on three key areas: Content-based multimedia analysis; Knowledge extraction; and Semantic multimedia. To ensure that the output of the targeted research becomes the primary feeding ground for industrial innovation, an Industrial Advisory Board with a core of four key industrial players has been set up and has been consulted from the very outset of proposal building. Its mission is to assist the network in defining research directions and to advise on potential exploitation of research results as they emerge. Specific dissemination objectives:

• Dissemination of the technical developments of the network across the broad research community
• Delivering the means to bring the results beyond the research community in a way that appeals to the EU citizen
• Enabling the non specialist multimedia user to feedback into the K-Space technological framework
• Influencing and contributing to related knowledge-based multimedia standardisation activities

DELTIO: Analysis of Multimedia Content using Evolutionary Ontologies and Application to Television News Bulletins, General Secretariat for Research and Technology, Infosociety, 2006-2007.

Objective of the project is the development of innovative techniques for the representation, analysis and extraction of semantic information for the manipulation of multimedia content, with emphasis on their application to television news bulletins. Research and development will concentrate on techniques that enable the automatic analysis of multimedia content and the extraction of knowledge, resulting in the (semi-) automatic creation of metadata, as well as provide support for smart, semantic search services. The final output of the project will be a system for the analysis of television new bulletins, which will provide intelligent search functionalities in archives of digital television material.