Earticle

초록

영어

Feature reduction are common techniques that used to improve the efficiency and accuracy of the document classification systems. The problems associated with these techniques are the highly dimensionality of the feature space and The difficulty of selecting the important features for understanding the document in question. The document usually consists of several parts and the important features that more closely associated with the topic of the document are appearing in the first parts or repeated in several parts of the document. Therefore, the position of the first appearance of a word and the compactness of the word considered as factors that determine the important features using the information within a document. This study, explored the impact of combining three feature weighting methods that depend on inverse document frequency (IDF), namely, Term frequency (TFiDF), the position of the first appearance of a word (FAiDF), and the compactness of the word (CPiDF) on the classification accuracy. In addition, we have investigated different feature selection techniques, namely, Information gain (IG), Goh and Low (NGL) coefficients, Chi-square Testing (CHI), and Galavotti-Sebastiani-Simi Coefficient (GSS) in order to improve the performance for Arabic document classification system. Experimental analysis on Arabic datasets reveals that the proposed methods have a significant impact on the classification accuracy, and in most cases the FAiDF feature weighting performed better than CPiDF and TFiDF. The results also clearly showed the superiority of the GSS over the other feature selection techniques and achieved 98.39% micro-F1 value when using a combination of TFiDF, FAiDF, and CPiDF as feature weighting method.

목차

Abstract
 1. Introduction
 2. Related Works
 3. Methodology
  3.1. Feature Extraction
  3.2. Feature Selection
  3.3. Feature Representation
  3.4. Classification Algorithm
 4. Experiment and Results
  4.1. Data Collection
  4.2. Experimental Configuration and Performance Measure
  4.3. Results and Analysis
 5. Conclusion
 References

키워드

저자

• Abdullah Ayedh [ School of Information Science and Engineering, Central south University, Changsha, Hunan (HN), 410000/ Time (UTC+8), China ]
• Guanzheng Tan [ School of Information Science and Engineering, Central south University, Changsha, Hunan (HN), 410000/ Time (UTC+8), China ] Corresponding author
• Hamdi Rajeh [ School of Information Science and Engineering, Hunan University, 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