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
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;
Conference_Titel :
Audio, Language and Image Processing (ICALIP), 2014 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4799-3902-2
DOI :
10.1109/ICALIP.2014.7009862
