DocumentCode
3696922
Title
A k-Highest Expert Text Classification Algorithm Based on Choquet Integral
Author
Shuchao Feng;Wenqian Shang;Yuqi Wang
Author_Institution
Sch. of Sci., Commun. Univ. of China, Beijing, China
fYear
2015
fDate
7/1/2015 12:00:00 AM
Firstpage
499
Lastpage
503
Abstract
In recent years, the research on text classification algorithm is still a hot topic in text mining. The KNN is a classic text classification algorithm. The rule of finding the nearest neighbors directly affects the performance and precision of categorization. In this paper, we mainly focus on distance measure and similarity. We propose a new text classification algorithm which combines KNN and Choquet integral. Choquet integral provides a new way to find the k-nearest neighbors. The result of experiment shows that the performance of this method is better than the classical distance measure or similarity measure.
Keywords
"Text categorization","Training","Classification algorithms","Measurement","Computer science","Q-factor","Algorithm design and analysis"
Publisher
ieee
Conference_Titel
Applied Computing and Information Technology/2nd International Conference on Computational Science and Intelligence (ACIT-CSI), 2015 3rd International Conference on
Type
conf
DOI
10.1109/ACIT-CSI.2015.95
Filename
7336115
Link To Document