Earticle

초록

영어

Text data classification and retrieval is an important field of artificial intelligence, but because of the different characteristics and different language syntax, classification and retrieval also will be different; classification and identification retrieval traditional text data, using training data and segmentation the algorithm does not consider the specific locale, it is often an error. To solve this problem, we propose a weighted feature-based classification method, according to this method, the text data can be quickly and accurately classify; experiments show that the proposed algorithm can effectively improve the accuracy and speed of classification and retrieval.

목차

Abstract
 1. Introduction 
 2. Related Works
  2.1. Text Categorization
  2.2. Weighting
 3. Feature Weighting Classification Algorithms
  3.1. Feature Dimension Reduction Algorithm
  3.2. Text Classification Algorithm 
 4. Experiment and Result Analysis 
  4.1. Word Frequency Combined 
  4.2. Word Relevance Computation and Data Noise Reduction
  4.3. The Experiment Design and Analysis 
 5. Conclusion
 References

키워드

저자

• Zhou Chengyi [ University of Science and Technology Liaoning, Anshan, Liaoning, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605