Lecture "Information Discovery: Knowledge Engineering and Digital Humanities"

Information
Classification: 
Master Informatik
Credits: 
5
Exam: 
oral
Regular Dates: 
Tuesday, 14:00-16:30
Mühlenpfordstraße 23 (Informatikzentrum), IZ 251
Contents
Contents: 

At the beginning, only a few people could access information in a digital way. Nowadays hundreds of millions of people use information systems every day when they use a web shop, a search engine or manage their e-mails.
At the moment information discovery plays an important role for managing data collections, processing and identifying relevant data, and supporting users analysing their personal interests (e.g. context, language, semantics, etc.).
Data Engineering principles are important for representing, presenting and understanding data that is generated by different systems. Knowledge Engineering refers to all aspects involved in building, maintaining and using knowledge-based systems to turn passive data into exploitable knowledge.
In this course the fundamentals of Data and Knowledge Engineering will be presented. The information system architecture will be explained within all its components and related application areas will be discussed. The basic concepts and more advanced techniques for natural language processing, information filtering and decision support will be shown. Furthermore, in-depth knowledge and competences in Data Science / Data Mining will be given.
All the methods and techniques can be applied in Digital Humanities. This is an interdisciplinary environment, where researchers can work together. It is based on different research fields, e.g. quantitative text analysis, information retrieval, text mining, subject-specific databases, corpus linguistics, visualization of complex data structures and provides user-oriented / user-centred representations of the data that can then be further analysed hermeneutically in the humanities.
At the end of the course, the students are provided within a rich and comprehensive catalogue of tools and techniques and can develop and understand information systems applying their knowledge for Data and Knowledge Engineering. They can also use mining techniques that can be applied for different purposes, especially for digital humanities.

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