DocumentCode
2408147
Title
Business Stakeholder Analyzer: An Automatic Classification Approach to Facilitating Collaborative Commerce on the Web
Author
Chung, Wingyan
Author_Institution
The University of Texas at El Paso
fYear
2005
fDate
03-06 Jan. 2005
Abstract
As the Web is used increasingly to share and disseminate information, business analysts and managers are challenged to understand stakeholder relationships. Traditional stakeholder analysis approaches fail to accommodate the rapid Web growth while existing business intelligence tools lack analysis capability. This paper proposes an automatic classification approach to business stakeholder analysis on the Web. Based on the approach, we developed a system called Business Stakeholder Analyzer to perform automatic classification of stakeholder types. Experimental results showed that, compared with humans, the system achieved better within-class accuracies in widespread stakeholder types such as "partner/sponsor/supplier" and "media/reviewer." It was more efficient than human classification. The encouraging findings suggest a promising future of our approach to facilitating knowledge sharing in collaborative commerce.
Keywords
Support Vector Machines; Web page classification; business intelligence; feature selection; neural network; stakeholder analysis; Business; Collaboration; Companies; Educational institutions; Failure analysis; Humans; Information analysis; Intelligent networks; Performance analysis; Web pages;
fLanguage
English
Publisher
ieee
Conference_Titel
System Sciences, 2005. HICSS '05. Proceedings of the 38th Annual Hawaii International Conference on
ISSN
1530-1605
Print_ISBN
0-7695-2268-8
Type
conf
DOI
10.1109/HICSS.2005.134
Filename
1385256
Link To Document