2019
DOI: 10.33889/ijmems.2019.4.2-041
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Sentiment Analysis of Amazon Products Using Ensemble Machine Learning Algorithm

Abstract: In recent years, Sentimental Analysis is used in all online product firms. The number of users using the particular product has increased which makes the industry to improvise the characteristics of the product. These days, many users who are using websites, blogs, online shopping tends to review the products they used. These reviews were taken into consideration by other users during their search for products. Hence the industry has found the root of delivering the correct product searched by the user based o… Show more

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Cited by 24 publications
(7 citation statements)
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“…In case the trial matches something the model has observed afore time, it can custom the ‘prior learning’, appraising the trial. The intention is to conceive a structure so that a platform is established for performing frequent advances over the prototype at the assigned task that is accustomed (Sadhasivam & Kalivaradhan, 2019; Suryawanshi et al, 2020).…”
Section: Machine Learningmentioning
confidence: 99%
“…In case the trial matches something the model has observed afore time, it can custom the ‘prior learning’, appraising the trial. The intention is to conceive a structure so that a platform is established for performing frequent advances over the prototype at the assigned task that is accustomed (Sadhasivam & Kalivaradhan, 2019; Suryawanshi et al, 2020).…”
Section: Machine Learningmentioning
confidence: 99%
“…Sentiment analyses are done with the help of the machine learning algorithms to classify the textual data detecting the polarity of the reviews about online products (amazon, IMBD, and any other dataset) using either machine learning methods or deep learning methods or in some cases integrating them. In the field of the sentiment analysis using the machine learning algorithms, the researchers in [4,5] focused on increasing the accuracy of the review classification. ey used the unigram and weighted unigram techniques.…”
Section: Literature Reviewmentioning
confidence: 99%
“…e classification is performed with finding the hyperplane that distinguishes between the two classes. On the other hand, [5] utilised the technique of "ensemble" machine learning algorithm that combines the predictions from the output of the classifiers NB and SVM together to produce more accurate predictions compared to an individual model. Dealing with the issue of performance, speed execution and accuracy created a better accurate system in contrast with the old systems.…”
Section: Literature Reviewmentioning
confidence: 99%
“…The accuracy of the proposed algorithm is calculated and compared with the accuracy of another existing algorithm such as k-Nearest Neighbor (kNN), Naive Bayes (NB) and Support Vector Machine (SVM) applied on same data set (Sadhasivam and Kalivaradhan, 2019). For instance, for the proposed algorithm a keyword "java free online" has been put by the user as a query and in return, he is getting the link of an e-learning site containing the java content.…”
Section: Accuracy= (Tp+tn)/ (Tp+fp+tn+fn)mentioning
confidence: 99%