2016
DOI: 10.1504/ijmso.2016.078105
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PROO ontology development for learning feature specific sentiment relationship rules on reviews categorisation: a semantic data mining approach

Abstract: Abstract:Crucial data like product features were obtained from consumer online reviews and sentiment words were gathered in Resource Description Format (RDF) in order to use them in meaningful reviews based categorisation on sentiments of the feature. The meaningful relationships among these pieces of RDF data are to be engineered in a Product Review Opinion Ontology (PROO). This serves as background knowledge to learn rule based sentiments expressed on product features. These semantic rules are learned on bot… Show more

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Cited by 5 publications
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“…The graph-based model RDF has been utilized to enhance a variety of tasks. The graph of an instance of RDF can be utilized to classify the sentience of review products, according to Santosh [8]. Using the graph concept to store, index and query vast volumes of provenance data was also advantageous, according to Chebot [9].…”
Section: Introductionmentioning
confidence: 99%
“…The graph-based model RDF has been utilized to enhance a variety of tasks. The graph of an instance of RDF can be utilized to classify the sentience of review products, according to Santosh [8]. Using the graph concept to store, index and query vast volumes of provenance data was also advantageous, according to Chebot [9].…”
Section: Introductionmentioning
confidence: 99%