Recommendation System by Analyzing User Review Using Machine Learning

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dc.contributor.advisorMohammad Monirujjaman Khan
dc.contributor.authorMd. Iqbal Hossain
dc.contributor.authorMd. Rahat Hossain
dc.contributor.authorFariha Ahmed Raha
dc.contributor.id1530260042
dc.contributor.id1530014042
dc.contributor.id1712823642
dc.coverage.departmentElectrical and Computer Engineering
dc.date.accessioned2026-01-08
dc.date.accessioned2026-01-08T05:46:10Z
dc.date.available2026-01-08T05:46:10Z
dc.date.issued2021
dc.description.abstractThis report presents the design and the implementation of Recommendation System by analyzing user reviews using machine learning. The system will filter using hybrid filtering (content based and collaborative) for users’ choices and analyzing reviews of users for that product, more items are recommended. It merged some categories of items from the dataset and used Truncated SVD (Singular value decomposition) to reduce the number of unnecessary features and dimensions of the dataset. It made a correlation between all the items with items purchased by the user based on items rated by other users who bought the same products. The algorithms are SVD, KNN and KNNWithMeans which has been applied to the system to make a model for recommendation. Overall, the system produced satisfactory results, successfully recommending top 10 products to users having the same taste of choice while also maintaining its design objectives of ring low cost and user friendly.
dc.description.degreeUndergraduate
dc.identifier.cd600000646
dc.identifier.print-thesisTo be assigned
dc.identifier.urihttps://repository.northsouth.edu/handle/123456789/1573
dc.language.isoen
dc.publisherNorth South Universty
dc.rights© NSU Library
dc.titleRecommendation System by Analyzing User Review Using Machine Learning
dc.typeThesis
oaire.citation.endPage38
oaire.citation.startPage1
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