This paper presents the solution to problem of summarizing Kazakh texts. The text summarization is considered as a sequence two tasks: extracting most important sentences and simplifying received sentences. task solved using TF-IDF method neural network technology “Seq2Seq”. Problem NMT for simplification was in absence dataset training. To solve this work propose use transfer learning method. ...

Text coherence evaluation becomes a vital and lovely task in Natural Language Processing subfields, such as text summarization, question answering, text generation and machine translation. Existing methods like entity-based and graph-based models are engaging with nouns and noun phrases change role in sequential sentences within short part of a text. They even have limitations in global coheren...

Automatic summarization is the process of reducing a text Document with a computer program in order to create a summary that retains the most important points of the original document. As The problem of information overload has grown, and as the quantity of data has increased, so has interest in automatic summarization. It is very difficult for human beings to manually summarize large documents...

Today, with digitally stored information available in abundance, even for many minor languages, this information must by some means be filtered and extracted in order to avoid drowning in it. Automatic summarization is one such technique, where a computer summarizes a longer text to a shorter non-rendundant form. Apart from the major languages of the world there are a lot of languages for which...