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Identifier 000379474
Title Context-Aware Multimedia Content Adaptation Framework
Alternative Title Προσαρμογή πολυμεσικής πληροφορίας με επίγνωση συμφραζομένων
Author Τρουλλινού, Γεωργία Σπυρίδων
Thesis advisor Πλεξουσάκης, Δημήτρης
Abstract Nowadays, people become more and more absorbed with media content. A large number of digital media files such as video, image and audio are generated, transmitted and stored every single moment. Additionally, the range of devices which are available to access media content becomes both increasingly heteroge¬neous and ubiquitous too. Users can receive content through a number of devices, which provide network connectivity but they have different properties. As a result, they expect to access the information according to their preferences and abilities without paying attention to restrictions regarding the time or the location. Conse¬quently, as the availability and consumption of multimedia content increases and in conjunction with the growing heterogeneity of devices, networks, users and delivery environment factors, the challenge of real time-content adaptation arises. This thesis proposes a context-aware multimedia content adaptation framework (ADF) that achieves the targets of ubiquitous access of multimedia information and personalization to the user's situation and preferences, overcoming any com¬patibility issues. Specifically, a set of upper-level ontologies provide a descriptive modelling of the context, exploiting the expressiveness of semantic technologies. Furthermore, a fundamental part of this modelling is the description of complex composition of multimedia content based on the MPEG-7 standard. The reasoning about the adaptation process is accomplished by multi-step decision rules, which are able to manage the captured knowledge and construct an adaptation plan. Fi¬nally, the proposed approach can be extended to different application domains by adding specific concepts and introducing new technologies.
Language English
Subject AMI
Multimedia Content
Issue date 2012
Collection   School/Department--School of Sciences and Engineering--Department of Computer Science--Post-graduate theses
  Type of Work--Post-graduate theses
Permanent Link https://elocus.lib.uoc.gr//dlib/5/4/3/metadata-dlib-1368689885-217008-29729.tkl Bookmark and Share
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