Using the KDSM methodology for knowledge discovery from a labor domain

The paper presents the knowledge discovery in serial measures (KDSM) methodology as an easy and optimal way for analyzing repeated very short serial measures with a blocking factor. An application to labor the domain is described using KDSM. A novel knowledge about labor domain´s behavior was obtained once KDSM was applied to this specific domain. KDSM is a hybrid methodology (statistic and artificial intelligence) that gives a possible solution to a knowledge problem, especially when seemingly there are no relevant attributes.