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.
Highlights
Every user’s browsing on the internet has reached as mammoth growth in e-commerce, social media, and online review sites especially in online shopping’s [1], [2]
Collaborative Filtering (CF) works on the belief that if two users have liked the same products in their past they are having similar likings.CF uses a new similarity measure to calculate most similar users for the target user and predict the product list for him
Collaborative filtering calculates the correct similarity between two users and can predict a list of products for the target user.CF works on the ratings given by user to their purchased products, so cannot predict the quality of products
Summary
Every user’s browsing on the internet has reached as mammoth growth in e-commerce, social media, and online review sites especially in online shopping’s [1], [2]. To seek other’s opinions to judge the product advantage is very important and for this Opinion Mining is used for extracting essential information from user comments or opinions in social networks regarding specific things or products. It is known as Sentiment Analysis (SA), it helps for various practical applications such as election result predictions, product’s benefits with prices, Share market profits etc. The aggregation of data mining and opinion has become a serious research topic to analyze user ratings and reviews before recommendation. Existing similarity measures used by CF to calculate similar users have some
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