Building knowledge discovery-driven models for decision support in project management

被引：16

作者：

García, MNM ^{[1
]}

Quintales, LAM ^{[1
]}

Peñalvo, FJG ^{[1
]}

Martín, MJP ^{[1
]}

机构：

[1] Univ Salamanca, Dept Informat & Automat, E-37008 Salamanca, Spain

来源：

DECISION SUPPORT SYSTEMS | 2004年 / 38卷 / 02期

关键词：

association rules; clustering; data mining; software size estimation; project management;

D O I：

10.1016/s0167-9236(03)00100-3

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Accurate estimations of software size in the early stages of a software project are critical in software project management because they lead to a good planning and reduce project costs. In this work, the relation between early software size measures as the function points and measures of the final product as the lines of code has been studied. A process to refine association rules, based on the generation of unexpected patterns, is proposed. The goal is to generate strong association rules between attributes that can be obtained early in the project and the final software size. (C) 2003 Elsevier B.V. All rights reserved.

引用

页码：305 / 317

页数：13

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