Title :
Data mining-based engineering project grading technique
Author :
Chang, Chunguang ; Song, Xiaoyu ; Gao, Bo ; Kong, Fanwen
Author_Institution :
Sch. of Manage., Shenyang Jianzhu Univ., Shenyang
Abstract :
The purpose of this paper is to improve the quality of engineering project grading, the basic processes of data mining technique are introduced. Taking the engineering project grading as background, the implement cycles such as business understanding, data understanding, data preparation, modeling, evaluation and deployment are studied in detail. During modeling, the decision tree is adopted as analyzing modeling, and the conventional C4.5 algorithm is adapted. The adapted algorithm is applied to the engineering project grading, and its result is compared with that of conventional C4.5 algorithm. The comparing result demonstrates that for the complex system such as engineering project grading, it can improve in a certain extent on precision and obtained structure of decision tree, it can improve the quality of engineering project grading.
Keywords :
business data processing; data mining; decision trees; engineering computing; C4.5 algorithm; data mining; engineering project grading; Data engineering; Data mining; Decision trees; Delta modulation; Engineering management; Intelligent control; Manufacturing automation; Manufacturing processes; Project management; Pulp manufacturing; C4.5 algorithm; Data mining; Decision tree; Engineering project; Grading;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4593487