Interactive Summarizer: Real-Time Personalized Document Summarization
Disciplines
Other Computer Engineering
Abstract (300 words maximum)
As today’s generation going on wheels, reading through lengthy paragraphs and contents like news articles and passages that required to be read for their work progression is quite not feasible and not time efficient. Whatever the existing text summarization tools available, provides quick overviews, yet they often lack user control and flexibility. This project, Interactive Summarizer: Real-Time Personalized Document Summarization, aims to address these gaps by focusing on a customizable abstractive summarization system. This tool allows users to upload a text file and choose whether to summarize an entire document or a specific part of the document, along with the adjustments in the length of the desired summary. Using the T5 transformer model, the system is going to generate eloquent, more human-like summaries which extracts the essence of the content rather than simply forming sentences from the original content. This model is cleaning the text using some preprocessing techniques like tokenization and generating real-time summary through an interactive interface. Inspired by recent advances in text summarization research, this project focuses on creating a user-friendly, efficient, and adaptable solution that enhances information accessibility and reading efficiency for text types.
Use of AI Disclaimer
no
Academic department under which the project should be listed
CCSE – Computer Science
Primary Investigator (PI) Name
Md Abdullah Al Hafiz Khan
Interactive Summarizer: Real-Time Personalized Document Summarization
As today’s generation going on wheels, reading through lengthy paragraphs and contents like news articles and passages that required to be read for their work progression is quite not feasible and not time efficient. Whatever the existing text summarization tools available, provides quick overviews, yet they often lack user control and flexibility. This project, Interactive Summarizer: Real-Time Personalized Document Summarization, aims to address these gaps by focusing on a customizable abstractive summarization system. This tool allows users to upload a text file and choose whether to summarize an entire document or a specific part of the document, along with the adjustments in the length of the desired summary. Using the T5 transformer model, the system is going to generate eloquent, more human-like summaries which extracts the essence of the content rather than simply forming sentences from the original content. This model is cleaning the text using some preprocessing techniques like tokenization and generating real-time summary through an interactive interface. Inspired by recent advances in text summarization research, this project focuses on creating a user-friendly, efficient, and adaptable solution that enhances information accessibility and reading efficiency for text types.