Title :
Text Classification Based on Rule Mining by Granule Network Constructing
Author :
Xia Zhang ; Yixin Yin ; Xiuyan Meng ; Hailong Zhao
Author_Institution :
Sch. of Inf. Eng., Univ. of Sci. & Technol. Beijing, Beijing
Abstract :
Text classification is one of the practices of knowledge discovery. Designation of the classifier is the most important par of text classification. Comparing with the methods based on statistic theory, classification based on rule learning is a better one on some situations. A granular computing approach is proposed to learn rules by constructing a granule network while classifying texts. The algorithm of constructing granule network is involved in a refining process that pick-up second-layer granules from the largest granule, third-layer granules from second-layer ones, repeat this procedure until get the smallest granules. During the work, the whole granule network is completed and text classification rules are learned.
Keywords :
artificial intelligence; data mining; text analysis; granular computing; granule network construction; knowledge discovery; refining process; rule learning; rule mining; text classification; Computer networks; Data mining; Fuzzy systems; Knowledge engineering; Logic; Machine learning; Nonhomogeneous media; Statistics; Text categorization; granular computing; granular network; rule; text classification;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
Conference_Location :
Shandong
Print_ISBN :
978-0-7695-3305-6
DOI :
10.1109/FSKD.2008.444