Email Dataset for Automatic Response Suggestion within a University

We have developed an application and
solution approach (using this dataset) for automatically generating and
suggesting short email responses to support queries in a university
environment. Our proposed solution can be used as one tap or one click solution
for responding to various types of queries raised by faculty members and
students in a university. Office of Academic Affairs (OAA), Office of Student
Life (OSL) and Information Technology Helpdesk (ITD) are support functions
within a university which receives hundreds of email messages on the daily
basis. Email communication is still the most frequently used mode of
communication by these departments. A large percentage of emails received by
these departments are frequent and commonly used queries or request for information.
Responding to every query by manually typing is a tedious and time consuming
task. Furthermore a large percentage of emails and their responses are consists
of short messages. For example, an IT support department in our university
receives several emails on Wi-Fi not working or someone needing help with a
projector or requires an HDMI cable or remote slide changer. Another example is
emails from students requesting the office of academic affairs to add and drop
courses which they cannot do it directly. The dataset consists of emails
messages which are generally received by ITD, OAA and OSL in Ashoka University.
The dataset also contains intermediate results while conducting machine
learning experiments.