Multimodal Aspect Opinion Mining using NER
This article describes the guidelines we use to analyze our opinions, including comments on text and multimedia (images) and the perception of entities and events. Identification is a subset of confidence analysis, which consists of specifying a comment in a comment, such as a specific review of a product or service, a reviewer, a compliment, or a complaint. We use POS tagging to tag individual words in verbal or non verbal terms. We also developed a set of linguistic forms for the same purposes and integrated them into the classifier. The traditional approach we take is a rule based approach, which we consider subset, taking into account problems that exist in the social colony, such as noisy syntax or misspellings, oaths, or patterns. Other words of skepticism, and so on. Multimedia content analysis makes this work perfect for solving ambiguity issues and providing other contextual information. The main task for this: First, the combination of new tools to extract information from text and multimedia; Secondly, the adaptation of the NLP tool for exploring specific information to solve the problem. The classifier combination with the embedded word model for confidence analysis helps our approach to better accuracy than modern methods.