Practical study on the semantic analysis algorithm based on text classification

2021 ◽  
Author(s):  
Lei Deng ◽  
Xingzhen Tao ◽  
Gaohua Tian
Keyword(s):  
Text Classification ◽  
Semantic Analysis ◽  
Analysis Algorithm

scholarly journals Employee Performance Evaluation Using Sentiment Analysis

2021 ◽  
Vol 11 (2) ◽  
pp. 2086-2095
Author(s):  
Dr.R. Sasikumar ◽  
Badi Alekhya ◽  
K. Harshita ◽  
O.S. Hema Sree
Keyword(s):  
Data Mining ◽  
Text Classification ◽  
Semantic Analysis ◽  
Employee Performance ◽  
Mining Activity ◽  
Analysis Program ◽  
Machine Learning Methods ◽  
Language Analysis ◽  
Polarity Change ◽  
Natural Language Analysis

Emotional analysis and data mining has become a hot topic in the field of data mining and natural language analysis as a solidly typed mining activity to analyze the concept of objects (i.e., emotion) expressed in the text. Emotional analysis is an important step in the recommendation process, because it allows you to separate the sense of the root context (e.g., positive or negative). In emotional analysis, the word-of-word (BOW) model is widely used in text classification, similar to how it is used in the modeling of a traditional theme. These two anti-emotional texts are considered very similar to the BOW representation. That is why, as a result of polarity change, machine learning methods often fail. We recommend combining a semantic analysis program with a separator to evaluate work results.

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