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The central idea is to produce a recommendation engine based on Natural Language Processing (NLP) methods. The recommendation engine would operate behind a website or a user service and feedback to the site details of what users are saying. This could be done automatically using a computer system. The system would learn what was said using empirical methods and control system methods. The engine would then be able to extract for meaning which could be used for commercial use or public use (for clients in the public sector). The engine would be usable behind different types of websites giving rise to wide applications. This opportunity has arisen now because we now have Big Data and a large volume of data would make a recommendation engine more effective as training sets can be produced.