  Efficient human resource management needs accurate assessment and
representation of available competences as well as effective mapping of
required competences for specific jobs and positions. In this regard,
appropriate definition and identification of competence gaps express
differences between acquired and required competences. Using a detailed
quantification scheme together with a mathematical approach is a way to support
accurate competence analytics, which can be applied in a wide variety of
sectors and fields. This article describes the combined use of software
technologies and mathematical and statistical methods for assessing and
analyzing competences in human resource information systems. Based on a
standard competence model, which is called a Professional, Innovative and
Social competence tree, the proposed framework offers flexible tools to experts
in real enterprise environments, either for evaluation of employees towards an
optimal job assignment and vocational training or for recruitment processes.
The system has been tested with real human resource data sets in the frame of
the European project called ComProFITS.

Computers and Society;Artificial Intelligence;Software Engineering;Social and Information Networks;Machine Learning