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Need of Sentiments Analysis with CF for Quality Recommendations

Seema P. Nehete, Satish R. Devane
European Journal of Electrical Engineering and Computer Science , Volume 5, pp 1-5; doi:10.24018/ejece.2021.5.2.284

Abstract: Recommendation system (RS) help user for purchasing the right product of their interest within the affordable right price. Presently many RS make use of only filtering methods to recommend products to the user which is not taking care of the quality of products. Quality of products can be found from textual reviews available on various e-commerce websites and hence this RS performs Sentiment Analysis (SA)of extracted relevant textual reviews along with Collaborative Filtering (CF) to give accurate and good quality recommendations to the user. Reviews are analyzed using optimized Artificial Neural Network (ANN) which shows notified improvement than traditional ANN on real-time extracted data of reviews.CF performance is proved by using the standard dataset of movilense used in many research papers. Results show high recall and accuracy of CF for the recommendation of products to the target user.
Keywords: Filtering / optimized / Recommendations / textual / Artificial Neural Network / Quality / Sentiments

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