Title :
Feature Extraction in Text Clustering Based on Theme
Author :
Shi, Nianyun ; Jing, Kong ; Xu, Jiuyun ; Duan, Yongxiang ; Li, Chunhua
Author_Institution :
Coll. of Comput. Sci. & Commun. Eng., China Univ. of Pet., Dongying
Abstract :
A new method is proposed, which refers to feature extraction based on oil theme of concept hierarchy to improve the weights between the high-frequency words and low-frequency words in the documents, and we use hash technology to improve the limitations of the theme of concept hierarchy. The method can identify the theme of texts accurately, and enhance the characteristic expression of texts. To a certain extent, it has resolved the semantic problem in specific areas.
Keywords :
feature extraction; pattern clustering; petroleum industry; text analysis; concept hierarchy; feature extraction; oil theme; petrochemical industry; text clustering; Application software; Computer science; Degradation; Educational institutions; Feature extraction; Frequency; Information technology; Ontologies; Petrochemicals; Petroleum; Feature Extraction; Text Clustering; Theme of Concept Hierarchy; Weight;
Conference_Titel :
Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3505-0
DOI :
10.1109/IITA.Workshops.2008.180
