文章基本信息

标题：The efficiency of algorithms DATA MINING "Close + and Extraction of association rules" for indexation 2D/3D and Selection of characteristic views
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作者：Mohamed El far ; Lahcen Moumoun ; Taoufiq Gadi 等
期刊名称：International Journal on Computer Science and Engineering
印刷版ISSN：2229-5631
电子版ISSN：0975-3397
出版年度：2010
卷号：2
期号：4
页码：1327-1331
出版社：Engg Journals Publications
摘要：This paper presents a new classification and search method of 3D object features views. This method is an application of algorithms: � Close+ for an object views classification purpose � Algorithm for extracting association rules in order to extract the characteristic view. We use the geometric descriptor of Zernike Moments to index 2D views of 3D object. The proposed method relies on a Bayesian probabilistic approach for search queries. The resulting outcome is presented by a collection of 120 3D models of the Princeton-based benchmark and then compared to those obtained from conventional methods.
关键词：Model 3D; indexation 3D; characteristic views; Zernike Moment; CLOSE+; association rules.