Course ObjectiveYou will get acquainted with the possibilities and problems of automatic
analysis of natural language by computers. Students will obtain
practical knowledge; they will learn to use existing technology and
experience the obstacles and options of the domain. They will learn
about the theories behind language technology and its connection to
artificial intelligence, linguistics and semantic web. The students will
choose a project themselves in which they apply the learned
technologies, evaluate its results and communicate their findings
through a report.
Course ContentIt is estimated that about 80% of knowledge is captured in language:
think of news, wikis, social media and handbooks. Searching for
information is also largely done through language. The amount of
information is too large for humans to oversee, which is why
technologies are developed to access and use this information more
Text Mining is a promising research domain whose goal it is to extract
structured information from unstructured natural language. This is a big
challenge as human language is a rich and complex medium that is to be
understood in the context of social human interaction. Therefore,
language technology analyses language on different levels: the
grammatical level (e.g. word types and syntax), and the semantic level
(e.g. entities, events, opinions). During the course you will learn how
this information is coded in text and how you can extract and present it
Teaching MethodsLectures (2 hours/week) and labs (2 hours/week).
Method of AssessmentAssignments and exam:
50% final assignment (group);
None of the grades can be lower than 5 to pass the course, the average
should be 5.5 or higher.
Attendance at the final assignment presentation session is mandatory and
all but one of the practical assignments need to be passed.
LiteratureWill be announced on Canvas
Target AudienceBA 3IMM, BA 3LI
Additional InformationThis course is also interesting to students from other faculties as many
fields deal with text and can benefit from automated text analysis (e.g.
digital humanities, financial domain). Specific prior knowledge is not
required, but affinity with computers is needed as the lab sessions and
assignment require some Python programming. Students need to work on
their laptops and Linux or Mac OS platforms are preferred.
Recommended background knowledgeInformation Retrieval and Python
|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|
dr. H.D. van der Vliet
dr. E. Maks
prof. dr. P.T.J.M. Vossen
You need to register for this course yourself
Last-minute registration is available for this course.
|Teaching Methods||Seminar, Lecture|
This course is also available as: