Extracting information from Emails

The project will attempt to extract useful information from emails as well as attempt to classify emails as meeting intent or not. The proposed project deals with attempting to leverage current machine learning and natural language processing techniques to build a prototype that can solve the above problems. This will benefit the company by not having to use manual solutions. Currently the company uses the mechanical turk which requires actual humans extracting information from the emails. The prototype would eliminate the need for this and reduce their costs.

Faculty Supervisor:

Dr. Osmar R. Zaiane

Student:

Kevin F Quinn

Partner:

Zenlike Inc.

Discipline:

Computer science

Sector:

Information and communications technologies

University:

University of Alberta

Program:

Accelerate

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