The term textmining is used analogous to data mining when the data is text. As there are some data specificities when handling text compared to handling data from databases, text mining has a number of specific methods and approaches. Some of these are extensions of data mining and machine learning methods, while other are rather text-specific. Text mining approaches combine methods from several related fields, including machine learning, data mining, information retrieval, natural language processing, statistical learning, and the Semantic Web. Basic text mining approaches are also extended to enable handling different natural languages ( cross-lingual text mining) and are combined with methods for handling different data types, such as links and graphs ( link mining and link discovery, graph mining), images and video (multimedia mining).