In the field of ontology mapping, using argumentation to combine different mapping approaches is an innovative research area. We had extended the Value-based Argumentation Framework (VAF) in order to represent arguments with confidence degrees, according to the similarity degree between the terms being mapped. The mappings are computed by agents using different mapping approaches. Based on their preferences and confidences, the agents compute their preferred mapping sets. The arguments in such preferred sets are viewed as the set of globally acceptable arguments. In previous work we had used discrete classes to represent the confidence degrees (certainty and uncertainty). In this paper, we propose to use continuous values from the interval [0,1]. Here, confidence is treated as strength. Using a threshold for the strength we can reduce the set of mappings and adjust the values of precision. We evaluate the use of strength against the previous confidence as discrete classes. The results are promising, especially what concerns precision.