DocumentCode
1798726
Title
Explore Hot Spots of City Based on DBSCAN Algorithm
Author
Xiaoqing Yu ; Yupu Ding ; Wanggen Wan ; Thuillier, Etienne
Author_Institution
Sch. of Commun. & Inf. Eng., Shanghai Univ., Shanghai, China
fYear
2014
fDate
7-9 July 2014
Firstpage
588
Lastpage
591
Abstract
Spatial clustering is one of the main methods of data mining and knowledge discovery. DBSCAN algorithm can be found in space with "noise" database clustering of arbitrary shape, is a kind of good clustering algorithm. This paper introduces the basic concept and principle of DBSCAN algorithm, and applies this algorithm to perform clustering analysis distributions of weibo location information. The article compare k-means algorithm with DBSCAN algorithm in order to prove the effectiveness of DBSCAN algorithm.
Keywords
data mining; pattern clustering; visual databases; DBSCAN algorithm; clustering algorithm; clustering analysis distribution; data mining; hot spots; k-means algorithm; knowledge discovery; noise database clustering; spatial clustering; weibo location information; Algorithm design and analysis; Cities and towns; Clustering algorithms; Data mining; Indexes; Noise; Spatial databases; DBSCAN algorithm; data mining; k-means algorithm; socialnetwork;
fLanguage
English
Publisher
ieee
Conference_Titel
Audio, Language and Image Processing (ICALIP), 2014 International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4799-3902-2
Type
conf
DOI
10.1109/ICALIP.2014.7009862
Filename
7009862
Link To Document