Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Online retailers routinely ask for feedback of the products and related services from their customers. Whilst e-commerce gets increasingly popular, the strength of customer evaluations for a product swiftly increases. A popular product may have several hundred reviews. As a result, it can be hard for a prospective consumer to read them and make a buying decision. The goal of this project is to aggregate every customer review of a certain product. This summary work is differ from typical text summarization in that we are only focused on certain qualities that consumers are enthusiastic about—and whether those opinions are either favourable or negative. We do not paraphrase the reviews by choosing or rephrasing a part of original statements from the reviews to emphasise their important points, as text summarization done in a traditional way. In this article, we solely mine opinions and product attributes that have received comments from reviewers. Numerous methods are offered to mine such features. Results from our trial indicate how highly successful these methods are.
"Amazon Review Sentiment Analysis ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 12, page no.690 - 695, December-2022, Available :http://www.ijrti.org/papers/IJRTI2212105.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator