DocumentCode :
2020737
Title :
Adaptive rules mining in ACVis based on ID3 algorithm in decision tree
Author :
Zenghong, Wu ; Yufen, Chen ; Jun, Zhang
Author_Institution :
Zhengzhou Inst. of Surveying & Mapping, Zhengzhou, China
Volume :
1
fYear :
2010
fDate :
17-18 July 2010
Firstpage :
446
Lastpage :
449
Abstract :
The adapted objects are multi-dimensional dynamic contexts in ACVis, and many adaptive rules, the foundation of ACVis context modeling and adaptivity, are contained in the hierarchical adaptive process. It´s urgent to understand the mechanism of hierarchical adaptivity and find adaptive rules mining methods. This article introduced the definition and gave out the categorization of multi-dimensional context. Based on which, illustrated the requirement and mechanism of hierarchical adaptivity. In order to satisfy the requirement, ID3 algorithm in decision tree was adopted for hierarchical context adaptive rules mining. A case study and extended application analysis show the great efficiency of ID3 algorithm in adaptive rules mining, parameters choosing and weight determination for context modeling and model matching.
Keywords :
data mining; decision trees; ACVis context modeling; ID3 algorithm; decision tree; hierarchical adaptive process; hierarchical context adaptive rules mining; model matching; multidimensional context; multidimensional dynamic contexts; weight determination; Computational modeling; Decision making; Navigation; ACVis; ID3 algorithm; context model; decision tree; hierarchical rules mining; multi-dimensional context;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Environmental Science and Information Application Technology (ESIAT), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7387-8
Type :
conf
DOI :
10.1109/ESIAT.2010.5568899
Filename :
5568899
Link To Document :
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