Abstract

The computerized examination of the feelings and evaluations of individuals concerning an entity or product is known as sentiment analysis, and it is carried out at the document, sentence, phrase, and function ranges. This method is used to accumulate customer remarks on quite a few products and services. Aspect-primarily based sentiment detection equipment deal with the opinions of customers regarding particular product capabilities. Nevertheless, the presentation of these outcomes in a manner this is each effective and concise is a hard project due to the numerous capabilities that a product may additionally possess. A quintessential part of Natural Language Processing (NLP), Sentiment Analysis (SA) makes it feasible to decipher the emotions expressed through humans in written words. Combining BERT with ontology-based totally sentiment evaluation is the focal point of this look at's investigation right into a hybrid technique. We advocate a combined device that makes use of BERT to supply better contextual facts and ontologies as structured lexicons for issue-based totally sentiment evaluation. By combining the electricity of BERT with the advantages of ontology-based strategies, we need to improve sentiment evaluation accuracy and offer more nuanced insights on person evaluations.