@misc{Dżega_Dorota_An_2009,
 author={Dżega, Dorota and Pietruszkiewicz, Wiesław},
 year={2009},
 rights={Wszystkie prawa zastrzeżone (Copyright)},
 description={Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu = Research Papers of Wrocław University of Economics; 2009; Nr 85, s. 96-105},
 publisher={Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu},
 language={eng},
 abstract={In this article we present an application of Artificial Intelligence in software project management by estimation of software metrics. Due to increasing significance of Open Source, we have selected project being hosted on the leading hosting platform of Open Source projects Source- forge.net. In the first part of the article, we describe steps of data extraction which was a large scale task because of the data source size and complexity. Moreover, we used data that were originally gathered to be used by project collaboration web-based system not to predict any features. Therefore extraction of meaningful data required an analysis of databases structure arid transformation of sets of records into the meaningful datasets. These datasets were constructed to predict four factors important to project management, i.e. skills, time, costs and effectiveness. In the later part of the article, we present the results of prediction experiments, that were performed using C4.5, RandomTree, CART, Neural Networks and Bayesian Belief Networks algorithms. Finally, we analyse influence of several methods' parameters on estimation accuracy and size of developed knowledge base.},
 title={An Empirical Study of Artificial Intelligence Support in Software Project Management},
 type={artykuł},
}