732A81 · 6 credits · Advanced level (A1F) · Statistik
Text Mining
Active · next start HT 2026
84%
passed the latest regular sitting
PRA1 · 17 Jan 2026 · 19 students
67%
passed the regular sittings, all sittings over the last 5 years
PRA1 · 72 students
Unusually easy in 2025/26
84% passed the ordinary exam in 2025/26 (19 students), against 60% on average in earlier years (53 students).
Hand-in or lab
PRA1 Examination
- A
- B
- C
- D
- E
- FX
- F
Main rounds
67% passed · 72 students
- 84%19
- 54%13
- 61%23
- 65%17
Later rounds
75% passed · 61 students
- 100%9
- 67%9
- 67%9
- 88%8
- 71%14
- 67%12
- Pass a later round: 75% (61 students), compared with 67% (72 students) on the ordinary exam
- Get B or A: 38% (133 students)
Show small sittings (7)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
- 75%4
- 100%1
- 100%1
- 75%4
- 100%1
- 100%3
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Hand-in or lab
LAB1 Laboratory work
- P
- F
Main rounds
78% passed · 117 students
- 100%29
- 78%23
- 72%39
- 62%26
Later rounds
62% passed · 21 students
- 50%6
- 50%6
- 78%9
- Pass a later round: 62% (21 students), compared with 78% (117 students) on the ordinary exam
Show small sittings (7)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
- 100%1
- 100%1
- 100%3
- 100%1
- 100%4
- 100%1
About the course
Aim
After completing the course, the student shall be able to
- implement text mining methods and apply them to practical problems
- analyze and summarize results from text mining experiments
- identify, formulate and solve problems within the area of text mining
- clearly present and discuss the conclusions of a project work
Content
The course covers the following methods within the area of text mining:
- information retrieval
- basic methods in language technology
- predictive modeling, in particular text classification
- text clustering and theme modeling
- information extraction
- validation methods
In addition, various applications of text mining as well as program libraries and data used in the field are treated.
- Examiner
- Marcel Bollmann
- Main field of study
- Statistik