Discovery of Association Rules between Factors Affecting User Satisfaction in Software Project by FP-GROWTH Algorithm
| Autor: | Sarun Intakosum, Katawut Kaewbanjong |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Association rule learning
business.industry Computer science User satisfaction Information technology 02 engineering and technology Software Confidence value Work (electrical) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Association rule discovery business Algorithm |
| Zdroj: | 2021 18th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON). |
| DOI: | 10.1109/ecti-con51831.2021.9454705 |
| Popis: | The main objective of this work was to find the association rules between factors affecting user satisfaction in software project by using an association rule discovery technique. Data from 191 software projects were collected and association rules between 15 Selected factors were discovered by FP–growth algorithm. Primarily, 281 association rules were discovered. Rules that were not directly related to user satisfaction were filtered out by simple criteria. In the end, 11 final association rules that passed those criteria were obtained with an average confidence value of 65.30%. These rules can incorporated in the planning and administration of a software project to gain utmost user satisfaction |
| Databáze: | OpenAIRE |
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