Text Mining Domains

2019-2020

Course Objective

Building a Reading Machine will give you the opportunity to apply all
you have learned so far in the master Text Mining in a hands-on use
case.

Course Content

Text Mining Domains is the follow-up of Applied Text Mining. In that
course you acquired the knowledge and the skills for mining large
amounts of text. In Text Mining Domains you will actually build a
so-called Reading Machine for a specific domain of your choice, to mine
valuable information.

Teaching Methods

interactive lectures and hands-on practical classes, 4 hrs per week.

Method of Assessment

This course is graded by a final report on a use case for your Reading
Machine.

Entry Requirements

Applied Text Mining

Target Audience

Master's students who passed Applied Text Mining

General Information

Course Code L_PAMATLW003
Credits 6 EC
Period P4
Course Level 400
Language of Tuition English
Faculty Faculty of Humanities
Course Coordinator prof. dr. P.T.J.M. Vossen
Examiner prof. dr. P.T.J.M. Vossen
Teaching Staff prof. dr. P.T.J.M. Vossen

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Seminar
Target audiences

This course is also available as: