|
| This Article | ||
| | ||
| Share | ||
| Bibliographic References | ||
| Add to: | ||
| | ||
| Search | ||
| ||
Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS'05) - Track 1
Big Island, Hawaii
January 03-January 06
ISBN: 0-7695-2268-8
| ASCII Text | x | ||
| Wingyan Chung, "Business Stakeholder Analyzer: An Automatic Classification Approach to Facilitating Collaborative Commerce on the Web," 2013 46th Hawaii International Conference on System Sciences, vol. 1, pp. 15c, Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS'05) - Track 1, 2005. | |||
| BibTex | x | ||
| @article{ 10.1109/HICSS.2005.134, author = {Wingyan Chung}, title = {Business Stakeholder Analyzer: An Automatic Classification Approach to Facilitating Collaborative Commerce on the Web}, journal ={2013 46th Hawaii International Conference on System Sciences}, volume = {1}, year = {2005}, issn = {1530-1605}, pages = {15c}, doi = {http://doi.ieeecomputersociety.org/10.1109/HICSS.2005.134}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - 2013 46th Hawaii International Conference on System Sciences TI - Business Stakeholder Analyzer: An Automatic Classification Approach to Facilitating Collaborative Commerce on the Web SN - 1530-1605 SP EP A1 - Wingyan Chung, PY - 2005 KW - stakeholder analysis KW - Web page classification KW - business intelligence KW - feature selection KW - neural network KW - Support Vector Machines VL - 1 JA - 2013 46th Hawaii International Conference on System Sciences ER - | |||
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.
Index Terms:
stakeholder analysis, Web page classification, business intelligence, feature selection, neural network, Support Vector Machines
Citation:
Wingyan Chung, "Business Stakeholder Analyzer: An Automatic Classification Approach to Facilitating Collaborative Commerce on the Web," hicss, vol. 1, pp.15c, Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS'05) - Track 1, 2005
Usage of this product signifies your acceptance of the Terms of Use.
