Journal of Science and Technology

URI vĩnh viễn cho bộ sưu tập này

https://oerrepository.ntt.edu.vn/handle/298300331/3

Duyệt qua

Đang duyệt Journal of Science and Technology theo Chủ đề

Đang hiển thị 1 - 3 trong tổng số 3
  • Hình ảnh thu nhỏ
    Tài liệu
    A Reformed K-Nearest Neighbors Algorithm for Big Data Sets
    (Trường Đại học Nguyễn Tất Thành (Tạp chí Khoa học công nghệ NTT), 2018-03-08) Vo, Ngoc Phu; Vo, Thị Ngoc Tran
    In This Research, We Propose An Improvement To K-NN To Process Big Datasets In A Shortened Execution Time. The Reformed K-Nearest Neighbors Algorithm (R-K-NN) Can Be Implemented On Large Datasets With Millions Or Even Billions Of Data Records. R-K-NN Is Tested On A Data Set With 500,000 Records. The Execution Time Of R-K-NN Is Much Shorter Than That Of K-NN. In Addition, R-K-NN Is Implemented In A Parallel Network System With Hadoop Map (M) And Hadoop Reduce (R).
  • Hình ảnh thu nhỏ
    Tài liệu
    English sentiment classification using a Gower-2 coefficient and a genetic algorithm With a fitness-proportionate selection in a Parallel network environment
    (Trường Đại học Nguyễn Tất Thành (Tạp chí Khoa học công nghệ NTT), 2018-02-28) Vo, Ngoc Phu; Vo, Thi Ngoc Tran
    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.
  • Hình ảnh thu nhỏ
    Tài liệu
    English Sentiment Classification using Only the Sentiment Lexicons with a Johnson Coefficient in a Parallel Network Environment
    (Trường Đại học Nguyễn Tất Thành (Tạp chí Khoa học công nghệ NTT), 2017-12-20) Vo, Ngoc Phu; Vo, Thi Ngoc Tran
    Sentiment classification is significant in everyday life, such as in political activities, commodity production and commercial activities. In this survey, we have proposed a new model for Big Data sentiment classification. We use many sentiment lexicons of our basis English Sentiment Dictionary (bESD) to classify 5,000,000 documents including 2,500,000 positive and 2,500,000 negative of our testing data set in English. We do not use any training data set in English