A Sting Algorithm and Multi-dimensional Vectors Used for English Sentiment Classification in a Distributed System

dc.contributor.author	Vo, Ngoc Phu
dc.contributor.author	Vo, Thi Ngoc Tran
dc.date.accessioned	2024-08-21T03:03:02Z
dc.date.available	2024-08-21T03:03:02Z
dc.date.issued	2017-12-20
dc.description	19 tr.
dc.description.abstract	In this research, we have proposed a new model for Big Data sentiment classification in the parallel network environment - a Cloudera system with Hadoop Map (M) and Hadoop Reduce (R). Our new model has used a Statistical Information Grid Algorithm (STING) with multi-dimensional vector and 2,000,000 English documents of our English training data set for English document-level sentiment classification. Our new model can classify sentiment of millions of English documents based on many English documents in the parallel network environment. However, we tested our new model on our testing data set (including 1,000,000 English reviews, 500,000 positive and 500,000 negative) and achieved 83.92% accuracy
dc.identifier.uri	https://oerrepository.ntt.edu.vn/handle/298300331/41
dc.language.iso	vi_VN
dc.publisher	Trường Đại học Nguyễn Tất Thành (Tạp chí khoa học công nghệ NTT)
dc.subject	Sentiment Classification
dc.subject	English Sentiment Classification
dc.subject	Opinion Mining
dc.title	A Sting Algorithm and Multi-dimensional Vectors Used for English Sentiment Classification in a Distributed System
dc.type	Article

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