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Adaptive Learning Process for the Evolution of Ontology-Described Classification Model in Big Data Context

2016

International audience; One of the biggest challenges in Big Data is to exploit value from large volumes of variable and changing data. For this, one must focus on analyzing the data in these Big Data sources and classify the data items according to a domain model (e.g. an ontology). To automatically classify unstructured text documents according to an ontology, a hierarchical multi-label classification process called Semantic HMC was proposed. This process uses ontologies to describe the classification model. To prevent cold start and user overload, the classification process automatically learns the ontology-described classification model from a very large set of unstructured text documen…

[ INFO ] Computer Science [cs]Computer scienceMaintenanceBig dataAdaptive learningContext (language use)Multi-label classification02 engineering and technologyOntology (information science)[INFO] Computer Science [cs]Machine learningcomputer.software_genreAdaptive LearningData modeling[SPI.AUTO]Engineering Sciences [physics]/AutomaticMachine LearningCold start020204 information systems[ SPI.AUTO ] Engineering Sciences [physics]/AutomaticMachine learning0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]Multi-Label ClassificationMulti-label classificationbusiness.industryOntologyOntology-based data integration[SPI.AUTO] Engineering Sciences [physics]/Automatic020201 artificial intelligence & image processingAdaptive learningArtificial intelligencebusinesscomputer
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