Abstract
Today’s world is a world of Internet, almost all work can be done with the help of it, from simple mobile phone recharge to biggest business deals can be done with the help of this technology. People spent their most of the times on surfing on the Web; it becomes a new source of entertainment, education, communication, shopping etc. Users not only use these websites but also give their feedback and suggestions that will be useful for other users. In this way a large amount of reviews of users are collected on the Web that needs to be explored, analyse and organized for better decision making. Opinion Mining or Sentiment Analysis is a Natural Language Processing and Information Extraction task that identifies the user’s views or opinions explained in the form of positive, negative or neutral comments and quotes underlying the text. Aspect based opinion mining is one of the level of Opinion mining that determines the aspect of the given reviews and classify the review for each feature. In this paper an aspect based opinion mining system is proposed to classify the reviews as positive, negative and neutral for each feature. Negation is also handled in the proposed system. Experimental results using reviews of products show the effectiveness of the system.
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