*Linked Open Data: State-of-the-Art Mechanisms and Conceptual Framework DOI: http://dx.doi.org/10.5772/intechopen.94504*

defined model that has "TrueTrace\_Fitness\_(TP)" and "FalseTrace\_Fitness\_(TN)" respectively.

> ( ) ( ) "TestLog\_ forSpecifiedClass and hasTraceFitness some 'TrueTrace\_Fitness\_ TP ". ( ) ( ) "TestLog\_ forSpecifiedClass and hasTraceFitness some 'FalseTrace\_Fitness\_ TN ".

Thus, as reported in **Table 1**, each results of the classification process for the discovered models, i.e., the true positives and true negatives traces, were determined.

From the results of the classification method (**Table 1**), we note for each run set of parameters retrieved from the model that the commission error, otherwise referred to as error-rate (false positives (FP) and false negatives (FN)) was null, thus, equal to 0. This means that the reasoner (classifier) did not make critical mistakes. For instance, a case whereby a trace could be considered to be an instance of a class while it is categorically an instance of another class. In the same vein, the work notes that the accuracy rate (i.e., true positives (TP) and true negatives (TN)) when determining the different traces and classifications was very high, thus, correct, and were consistently observed for all the test sets.
