Text Summarization: A Short History

Up until recently, the text summarization was accomplished using two steps. #1 identify the key sentences #2 put them together to generate the summary. In the 1950s, researchers manually crafted rules to identify the key sentences. In the 1990s, researchers used ML algorithms to craft rules to identify the key sentences. In the 2000s, researchers used graph algorithms to identify key sentences, after representing the text as a graph! In the 2010s, researchers used neural networks to identify the key sentences. From 2017 and onwards, researches having been using a neural network architecture called Transformer to generate new text that amazingly summarizes the original document.