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Dynamic Personalisation of Media Content
Benedita [email protected]
Jeremy [email protected]
Juan Carlos [email protected]
Ana Peleteiro
Fernando [email protected]
Summary
Introduction
Background
Network Architecture
System Overview
Current Status
Conclusion
Introduction
Framework for the dynamic personalisation of media content.
Players: Media content producers, media service distributors, and viewers.
Two sorts of video objects: User-selected stream and external streams.
Profiling of the viewers is continuously performed by the system.
The identification of the potential candidate objects is performed by an agent-based brokerage platform.
Summary
Introduction
Background
Network Architecture
System Overview
Current Status
Conclusion
BackgroundRelated Projects
COAST: Content-centric network overlay architecture linking content sources to content consumers, including content-aware retrieval, delivery and streaming.
CAM4HOME: Metadata enabled content delivery framework to support end users and commercial content providers to create and deliver rich multimedia experiences.
ACDC: User-aware content-delivery architecture for content navigation and personalisation based on semantics and clouding.
OMWeb: Personalised media objects constructed on the fly from distributed components and according to user preferences.
BackgroundRepresentation of Media Objects
MPEG-7: Standard developed by the Moving Picture Experts Group (MPEG) for the structural and semantic description of multimedia content.
MPEG-7 based ontologies: Harmony, SmartWeb, Boemie, DS-MIRF, Rhizomik, aceMedia Project RDFS and Core Ontology for Multimedia.
To adopt an MPEG-7 based ontology for the representation of all media content.
BackgroundPersonalisation and Filtering
Content-based Filtering (CBF): It uses the description of the resource and the user’s interests to provide recommendations.
Collaborative Filtering (CF): It usually considers the comparison of ratings, provided by the users to the resources, with other similar users (concerning their profile).
Collaborative Tagging (CT): It allows users to describe contents by means of tags and to share such description.
Case-based Reasoning (CBR): It focuses on inexact reasoning by a similarity measurement among cases.
BackgroundElectronic Brokerage
E-brokers: Electronic intermediaries that facilitate exchanges between buyers (consumers) and sellers (producers) by meeting the needs of both parties.
E-brokerages are still a relative new and poorly understood type of business.
The existing so-called media e-brokerage systems are mainly for resource allocation and not for media content delivery.
BackgroundInsertion of Video Objects
Frame-based overlays (objects are overlays images) and Object-based video (supported by MPEG-4 extensions).
Digital Media Broadcasting (DMB): It usually considers the comparison of ratings, provided by the users to the resources, with other similar users (concerning their profile).
Transmitted video objects are multiplexed via the Delivery Multimedia Integration Framework (DMIF).
Objects are related to each other in their video scene and in their temporal relationships by the Binary Interchange Format (BIFS) or through the Lightweight Application Scene Representation (LASeR).
The user-end equipment will reassemble the objects into the desired scene for playback to the user interface.
Summary
Introduction
Background
Network Architecture
System Overview
Current Status
Conclusion
Network Architecture
Potential network implementation
Integration server:
It receives the source video file from the head-end.
It will request and retrieve the externally acquired video objects from third party video object servers.
Selecting video:
The source metadata requirements.
The external video object metadata description.
The profile of the viewer.
Re-multiplexing and streaming.
Summary
Introduction
Background
Network Architecture
System Overview
Current Status
Conclusion
System Overview
Generic architecture
Video objects are MPEG-4 instances annotated in an MPEG-7 based OWL ontology.
Enterprise agents: Producers and distributors of media content modelled by autonomous intelligent agents.
They can publish, update and remove their service descriptions – metadata descriptions of the objects they hold or seek to insert in the viewer stream.
Any entity can discover, download and interact with any service (agent) automatically.
System Overview
Viewer profiling
To find the best possible objects to insert within the mainstream:
Users’ profiles as CBR cases containing information (personal and semantic data, and tag cloud).
Filtering techniques enhaced with collaborative tagging to search for recommended objects.
P2P scheme to perform distributed search.
System Overview
Brokerage platform (2 layers)
Top layer Agents representing the producers and distributors (enterprise agents and market profiler agent).
Bottom layer Agents constituting the marketplace, which is governed by the market agent and populated by delegate agents.
Summary
Introduction
Background
Network Architecture
System Overview
Current Status
Conclusion
Current Status
Framework is under development.
Brokerage platform JADE.
Ontology OWL.
Media components MPEG-7 based OWL ontology.
Currently types of markets Iterated Contract Net negotiation protocol.
Summary
Introduction
Background
Network Architecture
System Overview
Current Status
Conclusion
Conclusion
Ambitious solution to the dynamic media content personalisation challenge.
Scalable market model to cover the global media industry.
Based on existing standards.
Design concept Open, modular, and open source and Java based.
Semantic Web (ontology-based) approach for the knowledge representation intends to contribute to promote the interoperability with other systems and to allow future expansions.
Thanks for coming!
Benedita [email protected]
Jeremy [email protected]
Juan Carlos [email protected]
Fernando [email protected]
