Recurrent Neural Network based Text Summarization Techniques by Word Sequence Generation

Word sequence prediction is the word processing method that can be very useful for generating text summary by reducing the number of keystrokes when in need for typing words. So, mostly typing and summarizing a large text summary document is very complicated and is time consuming process. With a large and huge amount of data circulating in this digital data world, there is necessary to create and develop some machine learning algorithms that can automatically generate accurate summaries. Types of Neural Network and deep learning field techniques are the most popular and efficient method for automatic text summarization. This paper provides various methods and different datasets that may be used to generate text summaries automatically which reduces the time to manually type and summarize large text documents.