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- W2518441445 abstract "The recent growth of e-commerce websites has paved a way for the users to express their opinions on these web portals which, in turn, makes the customers review these comments before buying any product or service. The comprehensive reading of these large number of reviews is cumbersome and tiring. The purpose of this paper is to perform the analysis on the tourism domain reviews to decide whether the document is positive or negative. The traditional methods use a machine learning approach, but the authors are using an unsupervised dictionary based approach to classify the opinions. The scores of the opinions are extracted using Sentiwordnet, a popular dictionary for calculating the sentiment." @default.
- W2518441445 created "2016-09-16" @default.
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- W2518441445 date "2016-10-01" @default.
- W2518441445 modified "2023-09-25" @default.
- W2518441445 title "Classification of Polarity of Opinions Using Unsupervised Approach in Tourism Domain" @default.
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- W2518441445 doi "https://doi.org/10.4018/ijrsda.2016100105" @default.
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