Location
https://ccse.kennesaw.edu/computing-showcase/cday-programs/fall23program.php
Document Type
Event
Start Date
30-11-2023 4:00 PM
Description
Countless emails are sent and received daily, and a lot of time is spent reading through and understanding the content of these emails. This project aims to increase the efficiency of reading and gathering relevant email information. Our solution includes two parts: abstractive text summarization and action item extraction. Currently, these two items are common in different domains, however, they have not been combined and used with email understanding. Abstractive text summarization is the process of outputting the ideas of the emails using different words without giving quotes from the document. In this way, a person would be able to tell if the email is something they will need to look at and if not, then the Action Item Extractor tells what actions need to be performed, it involves finding all instances in a piece of text that are instructions, dates, or require something from the recipient. These two solutions hope to improve the efficiency of parsing through emails.
Included in
GR-485 Email Summarizer and Action Item Extractor
https://ccse.kennesaw.edu/computing-showcase/cday-programs/fall23program.php
Countless emails are sent and received daily, and a lot of time is spent reading through and understanding the content of these emails. This project aims to increase the efficiency of reading and gathering relevant email information. Our solution includes two parts: abstractive text summarization and action item extraction. Currently, these two items are common in different domains, however, they have not been combined and used with email understanding. Abstractive text summarization is the process of outputting the ideas of the emails using different words without giving quotes from the document. In this way, a person would be able to tell if the email is something they will need to look at and if not, then the Action Item Extractor tells what actions need to be performed, it involves finding all instances in a piece of text that are instructions, dates, or require something from the recipient. These two solutions hope to improve the efficiency of parsing through emails.