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 :
بازگشت