Name
Title | ||
|---|---|---|
On deriving actions for improving cost overrun by applying association rule mining to industrial project repository |
Abstract | ||
|---|---|---|
For software project management, it is very important to identify riskfactors which make project into runaway. In this study, we propose a method toextract improvement action items for a software project by applying associationrule mining to the software project repository for a metric of "cost overrun". Wefirst mine a number of association rules affecting cost overrun. We then groupcompatible rules, which include several common metrics having different values,from the mined rules and extract improvement action items of project improvement.In order to evaluate the applicability of our method, we applied our methodto the project data repository collected from plural companies in Japan. The resultof experiment showed that project improvement actions for cost overrun weresemi-automatically extracted from the mined association rules. We can confirmfeasibility of our method by comparing these actions with the results in the previousresearch. |
Year | Venue | Keywords |
|---|---|---|
2008 | ICSP | project improvement,improvement action item,software project management,software project,software project repository,association rule mining,method toextract improvement action,project improvement action,cost overrun,cost overrun weresemi-automatically,industrial project repository,project data,risk factors,association rule |
Field | DocType | Volume |
Systems engineering,Operations research,Software project management,Project management triangle,Information repository,Association rule learning,Software,Engineering,Basis of estimate,Cost overrun | Conference | 5007 |
ISSN | ISBN | Citations |
0302-9743 | 3-540-79587-1 | 0 |
PageRank | References | Authors |
0.34 | 11 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Junya Debari | 1 | 0 | 0.34 |
| Osamu Mizuno | 2 | 99 | 12.41 |
| Tohru Kikuno | 3 | 177 | 13.82 |
| N. Kikuchi | 4 | 79 | 6.84 |
| masayuki hirayama | 5 | 31 | 5.61 |