Business Intelligence Explorer: A Knowledge Map Framework for Discovering Business Intelligence on the Web
36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the (2003)
Big Island, Hawaii
Jan. 6, 2003 to Jan. 9, 2003
Wingyan Chung , University of Arizona
Hsinchun Chen , University of Arizona
Jay F. Nunamaker Jr. , University of Arizona
Nowadays, information overload hinders the discovery of business intelligence on the World Wide Web. Existing business intelligence tools suffer from a lack of analysis and visualization capabilities and traditional result list display by search engines often overwhelms business analysts with irrelevant information. Thus, developing tools that enable better analysis while reduce information overload has been a challenge. The literature show that hierarchical and map displays enable effective access and browsing of information. However, they have not been widely applied to discover business intelligence on the Web. This research proposes Business Intelligence Explorer, a tool implementing the steps in a knowledge map framework for discovering business intelligence on the Web. Two browsing methods, namely, Web community and knowledge map, have been implemented. Web community uses a genetic algorithm to organize different Web sites into a hierarchical format. Knowledge map uses a multidimensional scaling algorithm to place different Web sites as points on a map. Preliminary results of our user study show that Web community helps users locate results quickly and effectively. Users liked the intuitive map display of knowledge map. Our Business Intelligence Explorer contributes to alleviate information overload in business analysis. Future directions on applying document visualization techniques in discovering business intelligence are described.
Business intelligence, Web browsing, knowledge map, Web community, genetic algorithm, multidimensional scaling, visualization
W. Chung, J. F. Nunamaker Jr. and H. Chen, "Business Intelligence Explorer: A Knowledge Map Framework for Discovering Business Intelligence on the Web," 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the(HICSS), Big Island, Hawaii, 2003, pp. 10b.