English sentiment classification using a Gower-2 coefficient and a genetic algorithm With a fitness-proportionate selection in a Parallel network environment
| dc.contributor.author | Vo, Ngoc Phu | |
| dc.contributor.author | Vo, Thi Ngoc Tran | |
| dc.date.accessioned | 2024-08-21T03:17:34Z | |
| dc.date.available | 2024-08-21T03:17:34Z | |
| dc.date.issued | 2018-02-28 | |
| dc.description | 50 tr. | |
| dc.description.abstract | We have already studied a data mining field and a natural language processing field for many years. There are many significant relationships between the data mining and the natural language processing. Sentiment classification Has HAd many crucial contributions to many different fields in everyday life, such as in political Activities, commodity production, and commercial Activities. A new model using a Gower-2 Coefficient (HA) and a Genetic Algorithm (GA) with a fitness function (FF) which is a Fitness-proportionate Selection (FPS) has been proposed for the sentiment classification. This can be applied to a big data. | |
| dc.identifier.uri | https://oerrepository.ntt.edu.vn/handle/298300331/43 | |
| dc.language.iso | vi_VN | |
| dc.publisher | Trường Đại học Nguyễn Tất Thành (Tạp chí Khoa học công nghệ NTT) | |
| dc.subject | English Sentiment Classification | |
| dc.subject | Distributed System | |
| dc.subject | Gower-2 Similarity Coefficient | |
| dc.title | English sentiment classification using a Gower-2 coefficient and a genetic algorithm With a fitness-proportionate selection in a Parallel network environment | |
| dc.type | Article |