SluitenHelpPrint
Switch to English
Cursus: LET-REMA-LCEX06
LET-REMA-LCEX06
Text Mining
Cursus informatieRooster
CursusLET-REMA-LCEX06
Studiepunten (ECTS)6
Categorie-
VoertaalEngels
Aangeboden doorRadboud Universiteit; Faculteit der Letteren; Graduate School;
Docenten
Contactpersoon van de cursus
dr. I.H.E. Hendrickx
Overige cursussen docent
Docent
dr. I.H.E. Hendrickx
Overige cursussen docent
Docent
dr. S. Verberne
Overige cursussen docent
Collegejaar2016
Periode
PER 1-PER 2  (29-08-2016 t/m 29-01-2017)
Aanvangsblok
PER 1
Onderwijsvorm
voltijd
Opmerking-
Inschrijven via OSIRISJa
Inschrijven voor bijvakkersJa
VoorinschrijvingNee
WachtlijstNee
Plaatsingsprocedure-
Cursusdoelen

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) in the text mining area. Students can build models for a text mining machine learning algorithms and language data, and they can evaluate and report on the developed modules. 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).

Inhoud
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. Example key applications that have emerged from this melting pot are question answering, social media mining, and summarization. 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 mining problem in the second half of the course, resulting in a term paper. 

A mix of lectures and take home practical assignments.
Niveau
Research Master
Toetsinformatie
50% of the final grade is determined by a term paper (describing a text mining experiment) and 50% by the final written exam. In each case the score should at least be 5.5.
Voorkennis
NoneAvailability
This course is available only to students of the Research Master’s programme Language and Communication and the MSc programmes Artificial Intelligence and Data Science. Admission of students from other (research) masters and PhD students is subject to approval by the programme coordinator (please contact secr.researchmastershlcs@let.ru.nl).
Contact informatie
Dr. I.H.E. Hendrickx (i.hendrickx@let.ru.nl)
Aanbevolen materiaal
Literatuur
The weekly literature is announced on Blackboard.
Werkvormen
Hoorcollege
AanwezigheidsplichtJa

Toetsen
Written exam
Weging50
ToetsvormTentamen
GelegenhedenBlok PER 2, Blok PER 3

Term paper
Weging50
ToetsvormPaper
GelegenhedenBlok PER 2, Blok PER 3

SluitenHelpPrint
Switch to English