Research on Text Classification Based on Word Embedding
MA Li
LI Shasha
Abstract：Focusing on the problems of the low classification accuracy of traditional feature selection algorithm,an improved text feature selection algorithm is proposed based on word vector. The article takes microblog data as the research object to carry on the sentiment analysis. It forwards an assumption that the feature items which are similar to the ones have strong category distinguish ability,would also have strong ability to distinguish categories. It applies word embedding which Word2vec trains to the process of traditional feature selection,and expands the feature items appropriately according to the similarity relation between the word vec?tors.The experimental results show that the improved feature selection algorithm has better results in its classification accuracy.
Keywords：word embeddingfeature expansionWord2vectext classification
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 281-284,303 )