A decision support system utilizing a semantic agent
| Autor: | Vinaya Babu, Devika Mehta, Keshvi Khatri, Poorva Kaushil, S. S. Mantha, Radha Shankarmani |
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| Rok vydání: | 2010 |
| Předmět: |
Decision support system
business.industry Computer science media_common.quotation_subject Software prototyping Ontology (information science) Knowledge acquisition Project manager Software development process Excellence Problem domain Systems development life cycle Software engineering business Adaptation (computer science) Knowledge transfer media_common Agile software development |
| Zdroj: | 2010 IEEE International Conference on Software Engineering and Service Sciences. |
| DOI: | 10.1109/icsess.2010.5552340 |
| Popis: | The adaptabilty, rapidity, and focus on high quality solutions offered by agile methodology have lead to a paradigm shift in the software development process in many enterprises. Agile methodology is iterative in nature, with each iteration i.e. timebox lasting 2–6 weeks. Iterations involve small teams comprising 9–19 developers working through the entire software development life cycle. Agile methodology works on two basic principles. The first being regular adaptation to changing circumstances and the second -focus on technical excellence and good design and high quality code. The first principle accommodates that tasks in an agile project cannot be predicted more than a week in advance. Thus the need arises for project teams to incorporate experts in the problem domain, such that they are better equipped to handle changes rapidly. However this methodology has been criticised as it may not bring about the benefits intended by the second principle unless practised by skilled programmers, who can create high quality code. Hence a project manager should be equipped with a highly skilled team. We propose the utilization of a semantic agent [4], which will act on behalf of the project manager and suggest experts based on a set of parameters. Our semantic agent is based on a semantic matching algorithm [7]. This algorithm utilizes an ontology based similarity framework to make recommendations and suggest training paths to satisfy the requirements of the project manager. The agent uses this algorithm to recommend employees based on their expertise, past experience and availability. Further, based on recommendations made by the agent we classify employees as experts and non experts and suggest knowledge transfer [8] methods to upgrade their skills. |
| Databáze: | OpenAIRE |
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