Design of GA and Ontology based NLP Frameworks for Online Opinion Mining

摘要

Background: For almost every domain, a tremendous degree of data is accessible in anonline and offline mode. Billions of users are daily posting their views or opinions by using differentonline applications like WhatsApp, Facebook, Twitter, Blogs, Instagram etc.Objective: These reviews are constructive for the progress of the venture, civilization, state and even nation.However, this momentous amount of information is useful only if it is collectively and effectivelymined.Methodology: Opinion mining is used to extract the thoughts, expression, emotions, critics, appraisalfrom the data posted by different persons. It is one of the prevailing research techniques that coalesceand employ the features from natural language processing. Here, an amalgamated approach has beenemployed to mine online reviews.Results: To improve the results of genetic algorithm based opining mining patent, here, a hybrid geneticalgorithm and ontology based 3-tier natural language processing framework named GAO_NLP_OM hasbeen designed. First tier is used for preprocessing and corrosion of the sentences. Middle tier is composedof genetic algorithm based searching module, ontology for English sentences, base words for thereview, complete set of English words with item and their features. Genetic algorithm is used to expeditethe polarity mining process. The last tier is liable for semantic, discourse and feature summarization.Furthermore, the use of ontology assists in progressing more accurate opinion mining model.Conclusion: GAO_NLP_OM is supposed to improve the performance of genetic algorithm based opinionmining patent. The amalgamation of genetic algorithm, ontology and natural language processingseems to produce fast and more precise results. The proposed framework is able to mine simple as wellas compound sentences. However, affirmative preceded interrogative, hidden feature and mixed languagesentences still be a challenge for the proposed framework.