Title :
Hierachical fuzzy set-based deep Web source classification
Author :
Wang Hai-long ; Yue Liang ; Zhao Peng-Peng ; Cui Zhi-Ming
Author_Institution :
Inst. of Intell. Inf. Process. & Applic., Soochow Univ., Suzhou, China
Abstract :
This paper presents a classification method of data source using fuzzy set and probabilistic model. The words of each domain are classified into characteristic words and general words according to their contribution to the current domain. The fuzzy set is introduced into the simplification process of characteristic words and the common words as the normalized glossary tool, which can be able to find more precise glossary in the homepage text. And a vocabulary probabilistic model is build after the normalized process in various domains, these words are classified by calculating the distance between the data source form vector and each domain vector.
Keywords :
Internet; classification; fuzzy set theory; glossaries; probability; text analysis; vocabulary; characteristic word; common word; data source form vector; deep Web source classification; domain vector; general word; hierarchical fuzzy set; homepage text; normalized glossary tool; vocabulary probabilistic model; Application software; Classification tree analysis; Databases; Electronic mail; Fuzzy sets; Information processing; Internet; Sea surface; Terminology; Vocabulary; deep Web; hierarchical fuzzy set; source classification;
Conference_Titel :
Computer Design and Applications (ICCDA), 2010 International Conference on
Conference_Location :
Qinhuangdao
Print_ISBN :
978-1-4244-7164-5
Electronic_ISBN :
978-1-4244-7164-5
DOI :
10.1109/ICCDA.2010.5541144