In this paper we present two experiments conducted for comparison of different language identification algorithms. Short words-, frequent words- and n-gram-based approaches are considered and combined with the Ad-Hoc Ranking classification method. The language identification process can be subdivided into two main steps: first a document model is generated for the document and a language model for the language; second the language of the document is determined on the basis of the language model and is added to the document as additional information. In this work we present our evaluation results and discuss the importance of a dynamic value for the out-of-place measure.