Abstract
Affiliate marketing is a transaction of purchasing or buying and selling anything online. E-commerce helps the customers to get over the difficulties of geographical and also helps the customers to purchase anytime and from any place including with these ideas even consumers or sellers have the advantage to review their product as positive or negative based on the reviews found online. The reviews of purchaser and seller are essential in finding the aspect and feature of the product which makes a helping hand to the firm and the purchaser. To find the product aspect rank the methodology are the reviews are extracted and pre-processing those extracted reviews, finding exact product aspect, splitting reviews into positive comments, negative comments and neutral comments. Using the sentimental classification technique and implementing the rank algorithm for ranking the product. In the data preprocessing there are methods available in which it initially differentiate the meaning and meaningless words and also it removes the postfix from each word and then tokenize each sentence by removing the emotion icons and also space. Aspect identification will help in identifying the aspect from the countless comments or reviews which is given by the purchaser or seller whether it is positive or negative and based on these high or low points will be generated with these points ranking is done. The working of sentimental classifier is to split and classify the comments of reviewer. The aspect of a product and opinions of consumers with the points gives the products aspects ranking and in its application.
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Lakshana, B., Tasneem Sultana, S., Samyuktha, L., Valarmathi, K. (2020). Product Aspect Ranking and Its Application. In: Hemanth, D.J., Kumar, V.D.A., Malathi, S., Castillo, O., Patrut, B. (eds) Emerging Trends in Computing and Expert Technology. COMET 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 35. Springer, Cham. https://doi.org/10.1007/978-3-030-32150-5_99
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DOI: https://doi.org/10.1007/978-3-030-32150-5_99
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