BLEU, ROUGE, and a textual entailment method. We have also done an in-depth discussion of the three evaluation techniques used, and have systematically proved the advantages of using a semantic-based evaluation technique to calculate the overall summarization score of a text document....
Specifically focusing on the landscape ofive text summarization, as opposed to extractive techniques, this survey presents a comprehensive overview, delving into state-of-the-art techniques, prevailing challenges, and prospective research directions. We categorize the techniques into traditional sequence-to...
It creates words and phrases, puts them together in a meaningful way, and along with that, adds the most important facts found in the text. This way, abstractive summarization techniques are more complex than extractive summarization techniques and are also computationally more expensive. Comparison ...
andevaluatetheproposedtechniquesforlargedocumentsum-marization.Furthermore,wefoundthesetechniquestobehighlyeffective,whichisnotthecasewithexistingtechniques.CCSCONCEPTS•Informationsystems→Summarization;•Computingmethod-ologies→Neuralnetworks;Semi-supervisedlearningsettings;KEYWORDSTextSummarization;RecurrentNeural...
this paper also provides an assessment of existingstate-of-the-art techniques relevant to domain-specif i c text summarization to address the research gaps.1 INTRODUCTIONWith the ever-increasing amount of textual data be-ing created, stored, and digitized, companies and re-searchers have large cor...
Hierarchical approaches have been used in several text classification tasks [23, 43], whereas few of them have been applied to the abstractive summarization task. In particular, we encode the input document in a hierarchical way from word-level to sentence-level. There are two advantages of ...
Disclosed RNN-implemented methods and systems for abstractive text summarization process input token embeddings of a document through an encoder that produces encoder hidden states;
Techniques for training for and performing abstractive text summarization are disclosed. Such techniques include, in some embodiments, obtaining textual content, and generating a reconstruction of the textual content using a trained language model, the reconstructed textual content comprising an abstractive ...
Comparative Analysis of Deep Learning-Based Abstractive Text Summarization Techniquesdoi:10.1007/978-981-19-2894-9_39In this digital era, a vast amount of information is generated; it is very difficult to get the information faster and more efficiently. In today's time, everyone needs more ...
In this paper, we propose a text summarization model using NLP techniques that can understand the context of the entire text, identify the most important portions of the text, and generate coherent summaries.Ramesh, G. S.VNRVJIETVamsi Manyam...