The Detection Of Spam in Various OM Through Ontological Method

Many individuals use the opinions posted on social media these days when deciding what goods or services to purchase. Opinion spam identification is a challenging task because individuals and organizations can both create bogus evaluations for various reasons. They create fictitious reviews to deceive readers or use automation to trigger the detection system by elevating or lowering the status of the target products to harm their reputations or boost them. In this work, we offer a novel method to detect opinion spam with good accuracy by leveraging knowledge-based Ontology.