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 :
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