Title :
The Research of kNN Text Categorization Algorithm Based on Eager Learning
Author :
Dong, Tao ; Cheng, Weinan ; Shang, Wenqian
Author_Institution :
Sch. of Comput., Commun. Univ. of China, Beijing, China
Abstract :
Text categorization is a fundamental methodology of text mining and it is also a hot topic of the research of data mining and web mining in recent years. It plays an important role in business, government decision-making management, scientific research, and so on. This paper presents an improved algorithm of text categorization which combines eager learning with kNN classification. Experimental results show that the improved algorithm not only improve the efficiency of categorization, but also significantly increase the accuracy of categorization and produce a qualitative leap on the practical value of the sensitive information system.
Keywords :
Internet; data mining; learning (artificial intelligence); pattern classification; security of data; text analysis; Web mining; data mining; eager learning; kNN classification; kNN text categorization algorithm; sensitive information system; text mining; Algorithm design and analysis; Computational modeling; Computers; Educational institutions; Text categorization; Training; Vectors; Eager learning; Text categorization; kNN;
Conference_Titel :
Industrial Control and Electronics Engineering (ICICEE), 2012 International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4673-1450-3
DOI :
10.1109/ICICEE.2012.297
