This chapter introduces a novel evolutionary model for intelligent text mining. The model deals with issues concerning shallow text representation and processing for mining purposes in an integrated way. Its aims are to look for interesting explanatory knowledge across text documents. The approach uses Natural-Language technology and Genetic Algorithms to produce explanatory novel hidden patterns. The proposed approach involves a mixture of different techniques from evolutionary computation and other kinds of text mining methods. Accordingly, new kinds of genetic operations suitable for text mining are proposed. Some experiments and results and their assessment by human experts are discussed which indicate the plausibility of the model for effective knowledge discovery from texts. With this chapter, authors hope the readers to understand the principles, theoretical foundations, implications and challenges of a promising linguistically-motivated approach to text mining.