A probabilistic abduction engine for media interpretation based on ontologies
RR'10 Proceedings of the Fourth international conference on Web reasoning and rule systems
Bootstrapping ontology evolution with multimedia information extraction
Knowledge-driven multimedia information extraction and ontology evolution
Ontology based information extraction from text
Knowledge-driven multimedia information extraction and ontology evolution
Logical formalization of multimedia interpretation
Knowledge-driven multimedia information extraction and ontology evolution
Ontology population and enrichment: state of the art
Knowledge-driven multimedia information extraction and ontology evolution
Structured data clouding across multiple webs
Information Systems
A reward-and-punishment-based approach for concept detection using adaptive ontology rules
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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The recent success of distributed and dynamic infrastructures for knowledge sharing has raised the need for semiautomatic/automatic ontology evolution strategies. Ontology evolution is generally defined as the timely adaptation of an ontology to changing requirements and the consistent propagation of changes to dependent artifacts. In this article, we present an ontology evolution approach in the context of multimedia interpretation. Ontology evolution in this context relies on the results obtained through reasoning for the interpretation of multimedia resources, through population of the ontology with new individuals or through enrichment of the ontology with new concepts and new semantic relations. The article analyses the results of interpretation, population and enrichment obtained in evaluation experiments in terms of measures such as precision and recall. The evaluation reveals encouraging results.