On completion of the course, you should be able to:

1. implement text mining methods and apply them to practical problems
2. analyse and summarise results from text mining experiments
3. identify, formulate and solve problems within the area of text mining
4. clearly present and discuss the conclusions of a project work

For each intended learning outcome, there is a set of more specific knowledge requirements that express what you need to demonstrate in order to attain a particular grade. These knowledge requirements are listed on the Examination page.

The course covers the following content:

• information retrieval
• basic methods in language technology
• predictive modelling, in particular text classification
• text clustering and topic modelling
• information extraction
• validation methods

The course is taught in the form of lectures, lab sessions, and supervision in connection with an individual project. You are also expected to study independently, both individually and in groups. When you plan your time for the course, you should calculate approximately

• 40 hours to prepare for, watch and follow-up on the video lectures
• 40 hours to prepare for, carry out and follow-up on the labs
• 80 hours to plan, carry out and document the project

You are entitled to individual project supervision during the study period you are registered for.

The course is co-taught with TDDE16 Text Mining at the Faculty of Science and Engineering.

The reading for this course consists of excerpts from the following books, as well as research articles.

• Daniel Jurafsky and James H. Martin. Speech and Language Processing. An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. Draft chapters of 3rd edition, December 2021.

• Christopher D. Manning, Prabhakar Raghavan, and Hinrich Schütze. Introduction to Information Retrieval. Cambridge University Press, 2008. The complete book is available on-line.

• ChengXiang Zhai and Sean Massung. Text Data Management and Analysis. A Practical Introduction to Information Retrieval and Text Mining. Morgan & Claypool, 2016. We will only use Chapter 1, which is available on-line.

What you can expect from us. We try our best to give you prompt, constructive, and meaningful feedback on how well you meet the knowledge requirements set out for the course. We offer feedback in various forms; you can find the details on the Examination page. Our focus is on formative feedback, which you can use to improve your learning (and we can use to improve our teaching!) while the course is ongoing.

What we expect from you. We expect you to familiarise yourself with the knowledge requirements set out for the course and to actively seek our feedback on how well you meet these requirements. We also expect you to reflect on the feedback we provide and grasp opportunities to put it to good use.

What we expect from you. This website is the primary source of information about the course, and we expect you to keep yourself up-to-date with what we publish here. We also send out information via the University’s email list for the course and the class team on Microsoft Teams, and we expect you to read these channels regularly while the course is ongoing.

What you can expect from us. When you contact us via email or chat, you can expect an answer during standard working hours, 8–17. (We do not respond to email/chat in the evening or weekend.) For more personal contact, you can talk to the examiner in class or book an appointment.

Accessibility. If there is any portion of the course that is not accessible to you due to challenges with technology or the course format, please let the examiner know so we can make appropriate accommodations.

Students with disabilities. If you have a documented disability, you should contact the examiner as soon as possible regarding accommodations. Book an appointment with the examiner