Learned Automatic Recognition Extraction

of Appointments from Email

Lauren Paone

Faculty Advisor: Fernando Pereira


Abstract:

Email has become one of the most prominent forms of communication. Many people receive an abundance of email each day making reading every email and extracting important information a very time consuming and tedious daily task. A lot of people use email as a means of scheduling appointments and notifying others of upcoming events. In this case, the recipient of the email must identify the details of the event and physically add them to a calendar or remember them. If a user does not have her calendar available as she is reading the email, she may forget to add the event.

This project involves trying to automate the extraction of important information regarding events and appointments from email. Specifically, two problems will be addressed. The first is identifying whether the email contains information about an event. Then, if there is information about an event, extracting things such as the title of event, the date, the time, and the location so that it could automatically be added to a calendar. To perform these tasks, the program has two separate components: a classifier and an extractor. The classifier takes email as input and outputs a label indicating whether or not the email contains an event. The emails that do contain events are input into the extractor and the title, date, time, and location is output. These components are combined to create a full system that takes emails as inputs and outputs event information. This system is integrated as part of Penns CALO project.


Paper

Poster


CIS Dept., University of Pennsylvania