Study of Abstractive Text Summarization Techniques

Nowadays, people use the internet to find information through information retrieval tools such as Google, Yahoo, Bing and so on. Because of the increasing rate of data, people need to get meaningful information. So, it is not possible for users to read each document in order to find the useful one. Among all the modern technologies, text summarization has become an important and timely tool for the users to quickly understand the large volume of information. Automatic text summarization system, one of the special data mining applications that helps this task by providing a quick summary of the information contained in the documents. Text summarization approach is broadly classified into two categories: extractive and abstractive. Many techniques on abstractive text summarization have been developed for the languages like English, Arabic, Hindi etc. But there is no remarkable abstractive method for Bengali text because individual word of every sentence accesses domain ontology & wordnet and it must require the complete knowledge about each Bengali word, which is lengthy process for summarization. It has thus motivated the authors to observe, analyze and compare the existing techniques so that abstractive summarization technique for Bengali texts can be proposed. To do so, the authors have conducted a survey on abstractive text summarization techniques on various languages in this paper. Finally, a comparative scenario on the discussed single or multi-document summarization techniques has been presented.