Automatic Text Summarization represents one of the most imperative and challenging applications of Natural Language Processing (NLP). Text Summarization extracts key information from a long text. Text ...

The resulting ROUGE scores establish the effectiveness of FastText against the baseline TF-IDF embedding. Our findings highlight the potential of sub-word-level semantic representations in enhancing ...

Introduction This project focuses on building a text summarization tool using various pre-trained models from the transformers library. The goal is to compare the performance of different models and ...

While text summarization aims to shorten long documents, simplification seeks to reduce the complexity of a document. To accomplish these tasks collectively, there is a need to develop machine ...

This project presents an implementation of text summarization using Python and the TextRank algorithm. Text summarization is a crucial task in natural language processing (NLP) that involves ...

ROUGE scores had been shown to be correlated with human evaluators and the ROUGE-L F 1 -score is the harmonic mean of the ROUGE-L recall and precision scores. In past research, the evaluations of many ...

Article citations More>> C.-Y. Lin, “ROUGE: A package for automatic evaluation summaries,” Proceedings of the Workshop on Text Summarization Branches Out, Barcelona, Spain, pp. 74–81, 25–26 July 2004.