IMGpedia: Enriching the Web of Data with Image Content Analysis

Abstract

Linked Data rarely takes into account multimedia content, which forms a central part of the Web. To explore the combination of Linked Data and multimedia, we are developing IMGpedia: we compute content-based descriptors for images used in Wikipedia articles and subsequently propose to link these descriptions with legacy encyclopaedic knowledge-bases such as DBpedia and Wikidata. On top of this extended knowledge-base, our goal is to consider a unified query system that accesses both the encyclopaedic data and the image data. We could also consider enhancing the encyclopaedic knowledge based on rules applied to co-occurring entities in images, or content-based analysis, for example. Abstracting away from IMG-pedia, we explore generic methods by which the content of images on the Web can be described in a standard way and can be considered as first-class citizens on the Web of Data, allowing, for example, for combining structured queries with image similarity search. This short paper thus describes ongoing work on IMGpedia, with focus on image descriptors.

Publication
In 10th Alberto Mendelzon International Workshop on Data Management and the Web
Sebastián Ferrada
Sebastián Ferrada
Assistant Professor

Research. Coffee. Lifting.