Multipedia: Enriching DBpedia with Multimedia Information

García-Silva, A. and Jakob, Max and Mendes, Pablo N. and Bizer, Christian (2011). Multipedia: Enriching DBpedia with Multimedia Information. In: "3rd The Sixth International Conference on Knowledge Capture, K-CAP 2011", 25/06/2011-29/06/2011, Banff, Alberta, Canada.

Description

Title: Multipedia: Enriching DBpedia with Multimedia Information
Author/s:
  • García-Silva, A.
  • Jakob, Max
  • Mendes, Pablo N.
  • Bizer, Christian
Item Type: Presentation at Congress or Conference (Article)
Event Title: 3rd The Sixth International Conference on Knowledge Capture, K-CAP 2011
Event Dates: 25/06/2011-29/06/2011
Event Location: Banff, Alberta, Canada
Title of Book: 3rd The Sixth International Conference on Knowledge Capture, K-CAP 2011
Date: June 2011
Subjects:
Freetext Keywords: oeg, España Virtual
Faculty: Facultad de Informática (UPM)
Department: Inteligencia Artificial
UPM's Research Group: Ontology Engineering Group – OEG
Creative Commons Licenses: None

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Abstract

Enriching knowledge bases with multimedia information makes it possible to complement textual descriptions with visual and audio information. Such complementary information can help users to understand the meaning of assertions, and in general improve the user experience with the knowledge base. In this paper we address the problem of how to enrich ontology instances with candidate images retrieved from existing Web search engines. DBpedia has evolved into a major hub in the Linked Data cloud, interconnecting millions of entities organized under a consistent ontology. Our approach taps into the Wikipedia corpus to gather context information for DBpedia instances and takes advantage of image tagging information when this is available to calculate semantic relatedness between instances and candidate images. We performed experiments with focus on the particularly challenging problem of highly ambiguous names. Both methods presented in this work outperformed the baseline. Our best method leveraged context words from Wikipedia,tags from Flickr and type information from DBpedia to achieve an average precision of 80%.

More information

Item ID: 6964
DC Identifier: http://oa.upm.es/6964/
OAI Identifier: oai:oa.upm.es:6964
Deposited by: Dr Oscar Corcho
Deposited on: 09 May 2011 10:25
Last Modified: 20 Apr 2016 16:04
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