Automatic Text Summarization Using Hybrid Fuzzy GA-GP

A novel technique is proposed for summarizing text using a combination of Genetic Algorithms (GA) and Genetic Programming (GP) to optimize rule sets and membership functions of fuzzy systems. The novelty of the proposed algorithm is that fuzzy system is optimized for extractive based text summarizing. In this method GP is used for structural part and GA for the string part (Membership functions). The goal is to develop an optimal intelligent system to extract important sentences in the texts by reducing the redundancy of data. The method is applied in 3 test documents and compared with the standard fuzzy systems as well as two other commercial summarizers: Microsoft word and Copernic Summarizer. Simulations demonstrate several significant improvements with the proposed approach.