DocumentCode
3125363
Title
Commodity Classification in Hierarchies
Author
Shen, Jie ; Chen, Cang ; Gao, Ying
Author_Institution
Inf. Eng. Coll., Yangzhou Univ., Yangzhou, China
fYear
2009
fDate
28-29 Dec. 2009
Firstpage
267
Lastpage
269
Abstract
In e-commerce transactions, goods are classified according to the hierarchical structure, which refers to a tree category. In the process of classification, we shall consider the special features. While using brand name for category, for instance, the degree of distinction characteristic of brand is higher. Based on this, we prepare a dictionary of brands for Chinese words segamentatin on one hand and use a kind of "discriminative naive Bayes classifier" model on the other hand. According to our experiment, we can get a result that the Naive bayes classification model is better than standard bayesian one.
Keywords
Bayes methods; electronic commerce; natural language processing; text analysis; word processing; Chinese words segmentation; brand name; commodity classification; discriminative naive Bayes classifier; e-commerce transactions; text classification; Bayesian methods; Classification tree analysis; Data mining; Dictionaries; Information systems; Niobium; Support vector machine classification; Support vector machines; Text categorization; Wireless networks; Commodity Classification; Discriminative Naive Bayes; Text Categorize;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Networks and Information Systems, 2009. WNIS '09. International Conference on
Conference_Location
Shanghai
Print_ISBN
978-0-7695-3901-0
Electronic_ISBN
978-1-4244-5400-6
Type
conf
DOI
10.1109/WNIS.2009.49
Filename
5381929
Link To Document