• Anusha s
• Dr Clara Kanamni A

In recent times, there is an massive amount of data available on the internet. With the enhance of knowledge, there is a need for summarization systems that will direct the person to the area they are paying attention in, without any waste of time. Automatic text summarization can solve this problem by generating summary automatically. It can be classified into extractive and abstractive text summarization techniques. Existing strategies of extractive summarization separate significant sentences from unique record and produce rundown with no alteration of genuine information. This system may not present clashing data appropriately. Abstractive summarization can take care of this issue by speaking to the extricated sentences into another reasonable semantic structure.Abstractive Sentence Summarization creates a shorter rendition of a given sentence while endeavoring to protect its importance. We present a conditional Recurrent neural network(RNN) which produces a synopsis of an information sentence..

LSTM, RNN, Abstractive summarization, Extractive Summarisation

"Survey on Abstractive Sentence Summarisation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.149-151, June 2019, Available :http://www.jetir.org/papers/JETIR1907R21.pdf

"Survey on Abstractive Sentence Summarisation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp149-151, June 2019, Available at : http://www.jetir.org/papers/JETIR1907R21.pdf