ProRankSys: Ranking consumer products by predicting opinion's weight on reviews
M. Arun Manicka Raja, S. Godfrey Winster, R. Saravanan, S. M. Swamynathan · 2014
The advancement of web has empowered e-commerce facilities and induced the intimidation of physical stores gradually. The online shopping space is growing all over the world. The consumers who mainly shop for products or services, before purchasing they wish to check for the product reviews that have been commented by other consumers. Therefore, analyzing the consumer reviews of online shopping is important to ease the future consumer's purchase. Generally, review analysis involves the process of determining the opinion polarity and then providing the results of performed analysis to the users by suggesting better products to users. Though various existing research methods are available for performing product analysis, it is important to reveal the individual opinion's weight by predicting the strength of each reviews and assessing the overall rank of the product by consolidating the predicted review strength. Therefore, the Online consumers can find out the reviews what they intended to attain quickly without searching all the reviews. The experimental result show that the proposed work yields better recommendation on products.