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Abstract
This work proposes an extension of aspect-based opinion mining approach in order to apply itto the tourism domain. The extension concerns with the fact that users refer differently to different kinds of products when writing reviews on the Web.Through a detailed study of on-line tourism product reviews, we found these features and then model them in our extension, proposing the use of new and more complex NLP-based rules for the tasks of subjective and sentiment classification at the aspect-level. We also entail the task of opinion visualization and summarization and propose new methods to help users digest the vast availability of opinions in an easy manner.User review is collected ,pos tagging is applied,then NLP rules is used .Next to find the opinion words based on the user aspect ,sentiment analysis and orientation is extracted sentiwordNet dictionary is used to find the positive and negative words.In this process aspect is identified, extracted and sentiment analysis is applied and then orientation is found ,finally result is generated.