Using a novel approach to cluster analysis to gain new valuable insights into software-project risk management.
Antonio J. AlencarLeucio T. CruzEber A. SchmitzArmando Leite FerreiraPublished in: BDIM (2008)
Keyphrases
- risk management
- cluster analysis
- software projects
- project management
- software development
- source code
- categorical data
- software engineering
- clustering algorithm
- risk assessment
- risk evaluation
- development process
- clustering method
- operational risk
- software development effort
- software systems
- software quality
- factor analysis
- data analysis
- software maintenance
- software development projects
- risk factors
- software project management
- data mining
- k means
- unsupervised learning
- data mining techniques
- commercial banks
- cluster validity
- effort estimation
- hierarchical latent class models
- project managers
- database systems
- artificial intelligence
- data sets
- e government
- pairwise
- similarity measure
- case study