DocumentCode
2396505
Title
Text categorization based on improved Rocchio algorithm
Author
Gao, Guanyu ; Guan, Shengxiao
Author_Institution
Dept. of Autom., Univ. of Sci. & Technol. of China, Hefei, China
fYear
2012
fDate
19-20 May 2012
Firstpage
2247
Lastpage
2250
Abstract
Text categorization is used to assign each text document to predefined categories. This paper presents a new text classification method for classifying Chinese text based on Rocchio algorithm. We firstly use the TFIDF to extract document vectors from the training documents which have been correctly categorized, and then use those document vectors to generate codebooks as classification models using the LBG and Rocchio algorithm. The codebook is then used to categorize the target documents using vector scores. We tested this method in the experiment and the result shows that this method can achieve better performance.
Keywords
natural language processing; text analysis; vectors; Chinese text; LBG; TFIDF; codebooks; improved Rocchio algorithm; target documents; text categorization; text classification method; text document; training documents; vector scores; Algorithm design and analysis; Classification algorithms; Computational modeling; Support vector machine classification; Text categorization; Training data; Vectors; LBG; Rocchio Algorithm; TFIDF; Text Categorization;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems and Informatics (ICSAI), 2012 International Conference on
Conference_Location
Yantai
Print_ISBN
978-1-4673-0198-5
Type
conf
DOI
10.1109/ICSAI.2012.6223499
Filename
6223499
Link To Document