In this paper, we introduce a media decision taking engine (MDTE), enabling the automatic selection and/or rating of multimedia content versions, based on the available context information. The presented approach is fully semantic-driven, which means that we not only semantically model the context information, but also the decision algorithms themselve, which are represented in N3 Rules, a rule language that extends RDF. The decision rules are based on a rating function, supporting the specification of weights and affinity parameters for each environment property. Finally, we show how the MDTE is integrated in a media delivery platform, using the provisions of the existing Web infrastructure.
%0 Journal Article
%1 VanLanckerVanDeursenEtAl13mtaa
%A Van Lancker, Wim
%A Van Deursen, Davy
%A Verborgh, Ruben
%A Van de Walle, Rik
%D 2013
%J Multimedia Tools and Applications
%K v1205 springer paper ai adaptive multimedia semantic web rdf ontology rules zzz.th.c4
%N 1
%P 7-26
%R 10.1007/s11042-012-1032-1
%T Semantic Media Decision Taking Using N3logic
%V 63
%X In this paper, we introduce a media decision taking engine (MDTE), enabling the automatic selection and/or rating of multimedia content versions, based on the available context information. The presented approach is fully semantic-driven, which means that we not only semantically model the context information, but also the decision algorithms themselve, which are represented in N3 Rules, a rule language that extends RDF. The decision rules are based on a rating function, supporting the specification of weights and affinity parameters for each environment property. Finally, we show how the MDTE is integrated in a media delivery platform, using the provisions of the existing Web infrastructure.
@article{VanLanckerVanDeursenEtAl13mtaa,
abstract = {In this paper, we introduce a media decision taking engine (MDTE), enabling the automatic selection and/or rating of multimedia content versions, based on the available context information. The presented approach is fully semantic-driven, which means that we not only semantically model the context information, but also the decision algorithms themselve, which are represented in N3 Rules, a rule language that extends RDF. The decision rules are based on a rating function, supporting the specification of weights and affinity parameters for each environment property. Finally, we show how the MDTE is integrated in a media delivery platform, using the provisions of the existing Web infrastructure.},
added-at = {2013-03-21T16:51:22.000+0100},
author = {Van Lancker, Wim and Van Deursen, Davy and Verborgh, Ruben and Van de Walle, Rik},
biburl = {https://www.bibsonomy.org/bibtex/2fdfe5a30d5e9a5b961c77a3da099bffa/flint63},
doi = {10.1007/s11042-012-1032-1},
file = {SpringerLink:2013/LanckerDeursenEtAl13mtaa.pdf:PDF},
groups = {public},
interhash = {45a1a197ae5036a65d317182638bf03e},
intrahash = {fdfe5a30d5e9a5b961c77a3da099bffa},
issn = {1380-7501},
journal = {Multimedia Tools and Applications},
keywords = {v1205 springer paper ai adaptive multimedia semantic web rdf ontology rules zzz.th.c4},
month = {#mar#},
number = 1,
pages = {7-26},
timestamp = {2018-04-16T11:46:40.000+0200},
title = {Semantic Media Decision Taking Using {N3logic}},
username = {flint63},
volume = 63,
year = 2013
}