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Multipedia: enriching DBpedia with multimedia information (2011)
| Content Provider | CiteSeerX |
|---|---|
| Author | García-Silva, Andrés Jakob, Max Mendes, Pablo N. Bizer, Christian |
| Description | 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%. |
| File Format | |
| Language | English |
| Publisher | ACM |
| Publisher Date | 2011-01-01 |
| Publisher Institution | In Proceedings of the sixth international conference on Knowledge capture, K-CAP ’11 |
| Access Restriction | Open |
| Subject Keyword | Semantic Relatedness Complementary Information Type Information User Experience Multimedia Information Dbpedia Instance Knowledge Base Linked Data Cloud Average Precision Audio Information Ambiguous Name Wikipedia Corpus Consistent Ontology Web Search Engine Ontology Instance Context Information Textual Description Major Hub Challenging Problem Candidate Image Method Leveraged Context Word |
| Content Type | Text |
| Resource Type | Article |