Text Summarization Using Adaptive Neuro-Fuzzy Inference System

Nowadays, data present on the World Wide Web is growing exponentially. People use search engines like Google, Bing, and Yahoo for retrieving the required information. But as the information present on the Web is huge, it is necessary for user to make the summary of this information. User can easily understand the large volume of data with the help of summary and does not require spending so many for analyzing the collected information. Text summarization is the process of transforming the large text into short and meaningful text. While summarizing the text, one should preserve its data matter and general message. It is laborious for individual person to summarize the large documents as it takes much time. It is a very difficult and time-consuming process for humans to summarize large documents. Different methods are used for summarizing the text till now like neural network, fuzzy logic, genetic algorithm, and many more. The proposed system is a hybrid system of neural network and fuzzy logic, which is known as adaptive neuro-fuzzy inference system. So it will overcome the drawbacks of both neural network and fuzzy logic. This proposed system takes the learning ability of neural network and uncertainty data handling of fuzzy system.