DocumentCode
2129198
Title
Research on incremental clustering
Author
Liu, Yongli ; Guo, Qianqian ; Yang, Lishen ; Li, Yingying
Author_Institution
Sch. of Comput. Sci. & Technol., Henan Polytech. Univ., Jiaozuo, China
fYear
2012
fDate
21-23 April 2012
Firstpage
2803
Lastpage
2806
Abstract
Currently, incremental document clustering is one the most effective techniques to organize documents in an unsupervised manner for many Web applications. This paper summarizes the research actuality and new progress in incremental clustering algorithm in recent years. First, some representative algorithms are analyzed and generalized from such aspects as algorithm thinking, key technique, advantage and disadvantage. Secondly, we select four typical clustering algorithms and carry out simulation experiments to compare their clustering quality from both accuracy and efficiency. The work in this paper can give a valuable reference for incremental clustering research.
Keywords
Internet; data mining; document handling; pattern clustering; Web applications; algorithm thinking; clustering quality; documents organization; incremental document clustering; key technique; representative algorithms; simulation experiments; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Clustering methods; Databases; Entropy; Internet; Web mining; algorithms; experiments; incremental clustering;
fLanguage
English
Publisher
ieee
Conference_Titel
Consumer Electronics, Communications and Networks (CECNet), 2012 2nd International Conference on
Conference_Location
Yichang
Print_ISBN
978-1-4577-1414-6
Type
conf
DOI
10.1109/CECNet.2012.6202079
Filename
6202079
Link To Document