Title :
Recent trends in Data Mining (DM): Document Clustering of DM Publications
Author :
Peng, Yi ; Kou, Gang ; Chen, Zhengxin ; Shi, Yong
Author_Institution :
Inst. of Inf. Sci., Technol. & Eng., Nebraska Univ., Omaha, NE
Abstract :
Data mining (DM) brings knowledge and theories from several fields including databases, machine learning, optimization, statistics, and data visualization and has been applied to various real-life applications. A large amount of data mining articles have been published. The goal of this study is to establish an overview of the past and current data mining research activities from the title and abstract more than 1400 textual documents collected from premier data mining journals and conference proceedings. Specifically, this study applied document clustering approaches to determine which subjects had been studied over the last several years, which subjects are currently popular, and describe the longitudinal changes of data mining publications
Keywords :
data mining; electronic publishing; pattern clustering; text analysis; data mining journal; data mining publication; document clustering; text categorization; Conference proceedings; Data engineering; Data mining; Data visualization; Delta modulation; IEL; Machine learning; Software libraries; Statistics; Visual databases; Categorization; Content analysis; Data mining field; Document Clustering;
Conference_Titel :
Service Systems and Service Management, 2006 International Conference on
Conference_Location :
Troyes
Print_ISBN :
1-4244-0450-9
Electronic_ISBN :
1-4244-0451-7
DOI :
10.1109/ICSSSM.2006.320794