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Abstractive Text Summarization and Unsupervised Text Classifier
2020In this day and age, as the Internet gets increasingly cluttered for content, the comprehension of generated huge texts is growingly becoming a source of major inconvenience for a normal viewer, and classifying it is another gruesome task. Text summarization and classification prove to be a boon as it abridge and categorize the massive text into ...
null Aditya +2 more
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A survey on abstractive text summarization
2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT), 2016Text Summarization is the task of extracting salient information from the original text document. In this process, the extracted information is generated as a condensed report and presented as a concise summary to the user. It is very difficult for humans to understand and interpret the content of the text.
N. Moratanch, S. Chitrakala
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Study on Abstractive Text Summarization Techniques
2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE), 2020As there is an increase in the usage of digital applications, the availability of data generated has increased to a tremendous scale. Data is an important component in almost every domain where research and analysis are required to solve the problems. It is available in a structured or unstructured format.
Parth Rajesh Dedhia +4 more
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Abstractive Summarization on Dynamically Changing Text
2021 5th International Conference on Computing Methodologies and Communication (ICCMC), 2021With abundant user data and computing power, using machine learning to automate or minimize our task has become a recent trend. These resources are useful in providing some correlations between data and drawing conclusions. There has been a rapid progression in the field of AI/ML since the past decade with areas like computer vision and natural ...
Rahul Rawat +3 more
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Abstractive Text Summarization Using Artificial Intelligence
SSRN Electronic Journal, 2019Text summarization is the process of creating concise summary of text. There are two main approaches to summarization namely extractive and abstractive method. Most of the system summaries use extractive method. Amongst few abstractive models available there are two models namely sequence to sequence and LSTM bidirectional model.
Chandu Parmar +2 more
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Abstractive Text Summarization
2022The objective of this project is to imitate the fundamental concepts of this research of state-of-the-art abstract text repeated models to examine various processes until the work had a reasonable functional basis. This work was motivated by various research papers with several novel features that have achieved remarkable achievement.
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An approach to abstractive text summarization
2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR), 2013Abstractive summarization is the technique of generating a summary of a text from its main ideas, not by copying verbatim most salient sentences from text. This is an important and challenge task in natural language processing. In this paper, we propose an approach to abstractive text summarization based on discourse rules, syntactic constraints, and ...
Huong Thanh Le, Tien Manh Le
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Abstractive Text Summarization on Templatized Data
2021Abstractive text summarization generates a brief form of an input text from the original source without the sentences being reused by still preserving the meaning and the important information. This could be modelled as a sequence-to-sequence learning by exploiting Recurrent Neural Networks (RNN).
C. Jyothi, M. Supriya
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Abstractive Text Summarization using Deep Learning
2022In current era, organizing the data has been a very tedious process as there is a lot of data growing every day and storing and managing them is getting tougher, to solve this problem one of the ways is to summarizing the data which in turn will save lot of storage and makes managing data easier. In this paper we have looked into various techniques and
H M, Hemanth +4 more
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