Modelling text prediction systems in low- and high-inflected languages

Text prediction was initially proposed to help people with a low text composition speed to enhance their message composition. After the important advancements obtained in the last years, text prediction methods may nowadays benefit anyone trying to input text messages or commands, if they are adequately integrated within the user interface of the application. Diverse text prediction methods are based in different statistic and linguistic properties of natural languages. Hence, they are very dependent on the language concerned. In order to discuss general issues of text prediction it is necessary to propose abstract descriptions of the methods used. In this paper a number of models applied to text prediction are presented. Some of them are oriented to low-inflected languages while others are for high-inflected languages. All these models have been implemented and their results are compared. Presented models may be useful for future discussion. Finally, some comments related to the comparison of previously published results are also done.