Name
Abstract | ||
|---|---|---|
Analytical knowledge is distributed among domain experts, analysts, and data-storage systems. Extracting such knowledge from databases is of interest to corporations. The traditional top-down development of corporate memory is not appropriate for modern organizations because of the distributed nature of information. This paper proposes models of analytical knowledge and new ways of developing corporate memory by using an extensible markup language (XML). It aims at efficient exploration of useful knowledge by mining the Web. The proposed approach of modeling analytical knowledge is explicit and sharable. The concepts introduced in the paper have been demonstrated with a manufacturing case study. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/TSMCA.2005.843391 | IEEE Transactions on Systems, Man, and Cybernetics, Part A |
Keywords | Field | DocType |
indexing terms,sustainability,data mining,top down,knowledge management,data storage,database management systems,extensible markup language,xml | Data science,XML,Domain knowledge,Business data processing,Computer science,Storage management | Journal |
Volume | Issue | ISSN |
35 | 5 | 1083-4427 |
Citations | PageRank | References |
7 | 0.51 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chun-Che Huang | 1 | 393 | 39.91 |
| Tzu-Liang Tseng | 2 | 7 | 0.85 |
| A. Kusiak | 3 | 724 | 111.33 |