Archaisms and neologisms identification in texts

Abstract

In this paper we present an application for identifying archaisms and neologisms in texts. The application also provides the ability to view graphically the evolution trends of these words for a better interpretation of the results. The presented solution consists of two phases: the learning phase in which we identify the general evolution trends of three categories of words (archaisms, neologisms and common words) and the classification phase in which we label new words with their corresponding category. For both phases, the application requires Internet access because it is using the Google Books N-gram Viewer to generate the images that back up the decisions.