K-Medoids algorithm 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 | 2024-08-21T08:21:41Z | |
| dc.date.available | 2024-08-21T08:21:41Z | |
| dc.date.issued | 2018-01-30 | |
| dc.description | 20 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 K-Medoids Algorithm (PAM) 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 85.98% accuracy. | |
| dc.identifier.uri | https://oerrepository.ntt.edu.vn/handle/298300331/56 | |
| dc.language.iso | vi_VN | |
| dc.publisher | Trường Đại học Nguyễn Tất Thành | |
| dc.subject | Computer and information | |
| dc.subject | Technologies | |
| dc.title | K-Medoids algorithm used for english sentiment classification in a distributed system | |
| dc.type | Article |