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Marco Arazzi, Marco Ferretti and Antonino Nocera
Huge quantities of audio and video material are available at universities and teaching institutions, but their use can be limited because of the lack of intelligent search tools. This paper describes a possible way to set up an indexing scheme that offer...
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Fahd A. Ghanem, M. C. Padma and Ramez Alkhatib
The rapid expansion of social media platforms has resulted in an unprecedented surge of short text content being generated on a daily basis. Extracting valuable insights and patterns from this vast volume of textual data necessitates specialized techniqu...
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Yuanyuan Li, Yuan Huang, Weijian Huang, Junhao Yu and Zheng Huang
An abstractive summarization model based on the joint-attention mechanism and a priori knowledge is proposed to address the problems of the inadequate semantic understanding of text and summaries that do not conform to human language habits in abstractiv...
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Moreno La Quatra and Luca Cagliero
The emergence of attention-based architectures has led to significant improvements in the performance of neural sequence-to-sequence models for text summarization. Although these models have proved to be effective in summarizing English-written documents...
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Marios Koniaris, Dimitris Galanis, Eugenia Giannini and Panayiotis Tsanakas
The increasing amount of legal information available online is overwhelming for both citizens and legal professionals, making it difficult and time-consuming to find relevant information and keep up with the latest legal developments. Automatic text summ...
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Pietro Dell?Oglio, Alessandro Bondielli and Francesco Marcelloni
Today, most newspapers utilize social media to disseminate news. On the one hand, this results in an overload of related articles for social media users. On the other hand, since social media tends to form echo chambers around their users, different opin...
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Jai Prakash Verma, Shir Bhargav, Madhuri Bhavsar, Pronaya Bhattacharya, Ali Bostani, Subrata Chowdhury, Julian Webber and Abolfazl Mehbodniya
The recent advancements in big data and natural language processing (NLP) have necessitated proficient text mining (TM) schemes that can interpret and analyze voluminous textual data. Text summarization (TS) acts as an essential pillar within recommendat...
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Ivan S. Blekanov, Nikita Tarasov and Svetlana S. Bodrunova
Abstractive summarization is a technique that allows for extracting condensed meanings from long texts, with a variety of potential practical applications. Nonetheless, today?s abstractive summarization research is limited to testing the models on variou...
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Mihai Alexandru Niculescu, Stefan Ruseti and Mihai Dascalu
Significant progress has been achieved in text generation due to recent developments in neural architectures; nevertheless, this task remains challenging, especially for low-resource languages. This study is centered on developing a model for abstractive...
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Jean Louis Ebongue Kedieng Fendji, Désiré Manuel Taira, Marcellin Atemkeng and Adam Musa Ali
Text summarization remains a challenging task in the natural language processing field despite the plethora of applications in enterprises and daily life. One of the common use cases is the summarization of web pages which has the potential to provide an...
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