Paper Info
Title
Multipedia: enriching DBpedia with multimedia information
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%.
Year
DOI
Venue
2011
10.1145/1999676.1999701
K-CAP
Keywords
Field
DocType
multimedia information,wikipedia corpus,context information,complementary information,audio information,challenging problem,enriching knowledge base,dbpedia instance,candidate image,type information,multimedia,ontology,knowledge base,linked data,user experience,semantic relatedness,image retrieval,web search engine
Semantic similarity,Ontology,Data mining,World Wide Web,User experience design,Search engine,Information retrieval,Computer science,Linked data,Knowledge base,Multimedia information,Cloud computing
Conference
Citations 
PageRank 
References 
5
0.66
23
Authors
4
Name
Order
Citations
PageRank
Andrés García-Silva149023.56
Max Jakob279730.27
Pablo N. Mendes3107051.09
Christian Bizer48448524.93