LET-REMA-LCEX06
Text and Multimedia Mining
Course infoSchedule
Course moduleLET-REMA-LCEX06
Credits (ECTS)6
Category-
Language of instructionEnglish
Offered byRadboud University; Faculty of Arts; Graduate School;
Lecturer(s)
Lecturer
dr. I.H.E. Hendrickx
Other course modules lecturer
Examiner
prof. dr. M.A. Larson
Other course modules lecturer
Lecturer
prof. dr. M.A. Larson
Other course modules lecturer
Coordinator
prof. dr. M.A. Larson
Other course modules lecturer
Contactperson for the course
prof. dr. M.A. Larson
Other course modules lecturer
Academic year2021
Period
PER 1-PER 2  (30/08/2021 to 30/01/2022)
Starting block
PER 1
Course mode
full-time
Remarks-
Registration using OSIRISYes
Course open to students from other facultiesYes
Pre-registrationNo
Waiting listNo
Placement procedure-
Aims
After successful completion of this course, students have an understanding, both at the conceptual and the technical level, of the application of natural language processing (NLP) and multimedia processing techniques to the areas of  text and multimedia mining. Students can design models for machine learning algorithms, and they can evaluate and report on the developed models. Also students understand, from a theoretical perspective, which tools are applicable in which situations, and which real-world challenges prevent the application of certain techniques (such as language variation and noise due to document processing errors or user interpretations). The course includes a set of assignments, which are designed to support student learning. Students are required to complete the assignments in order to pass the course.
Content
Text mining, also known as 'knowledge discovery from text', is an ICT research and development field that has gained increasing focus in the last decade, attracting researchers from computational linguistics, machine learning (an AI subfield), and information retrieval. Recently, text mining techniques been expanded to tackle other types of content, such as images, audio, and video. Example key applications that have emerged from this melting pot are question answering, social media mining, and summarization. The emphasis of the course is on text data, but other multimedia data are also covered. This course gives an overview of the field in a practical, hands-on fashion. In addition to the lectures, the students work on a self-chosen text or multimedia mining problem in the second half of the course, resulting in an individual research project paper. 
 
Level

Presumed foreknowledge

Test information

Specifics
This course consists of two parts: (1) lectures, readings, assignments, and exam and (2) a text and multimedia mining research project. You must pass both part in the same year, and cannot carry over one part to a future year. Note that if you only want to do the research project you can register for LET-REMA-LC1902 Text and Multimedia Research Project.
Required materials
Literature
Title:Literature includes scientific papers, which will be announced on BrightSpace and will be available online.

Instructional modes
At-home PER2 gel1
Attendance MandatoryYes

Lecture

Tests
Take home exam
Test weight50
Test typeProject
OpportunitiesBlock PER 2, Block PER 3

Minimum grade
5,5

Final paper
Test weight50
Test typeProject
OpportunitiesBlock PER 2, Block PER 3

Minimum grade
5,5