Adapting Semantic Web Information Retrieval to Multimedia

The amount of audio, video and image data on the Web is immensely growing, which leads to data management problems based on the hidden character of Multimedia. Therefore the interlinking of semantic concepts and media data with the aim to bridge the gap between the Internet of documents and the Web of Data has become a common practice. However, the value of connecting media to its semantic meta data is limited due to lacking access methods and the absence of an adapted query language specialized for media assets and fragments. This thesis aims to extend the standard query language for the Semantic Web (SPARQL) with media specific concepts and functions. The main contributions of the work are an exhaustive survey on Multimedia query languages of the last 3 decades, the SPARQL extension specification itself and an approach for the efficient evaluation of the new query concepts. Additionally I elaborate and evaluate a meta data based media fragment similarity approach, which provides a basis for further language extensions.

Level thesis:degree_level

thesis.doctoral

Grantor dc:publisher

Universität Passau

Year

2020

Author dc:creator

• Kurz, Thomas

Contributors dc:contributor

• Kosch, Harald
• Auer, Sören

• SPARQL
• Multimedia
• Semantic Web
• Web of Data
• SPARQL-MM

Statement dc:rights

• Creative Commons - CC BY - Namensnennung 4.0 International

Repository record source_url

https://opus4.kobv.de/opus4-uni-passau/frontdoor/index/index/docId/827

OAI identifier oai:identifier

oai:kobv.de-opus4-uni-passau:827