Masterstudium Business Informatics - Fakultät für Informatik, TU Wien
Masterstudium Business Informatics - Fakultät für Informatik, TU Wien
Masterstudium Business Informatics - Fakultät für Informatik, TU Wien
You also want an ePaper? Increase the reach of your titles
YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.
• Knowledge modeling<br />
Competences:<br />
• Group work<br />
• Knowledge sharing<br />
• Innovation of knowledge processes<br />
Syllabus: Objectives and problems of knowledge management in enterprizes and other<br />
organizations; process model for knowledge management; competence management; methods<br />
and systems for knowledge management; knowledge acquisition and engineering;<br />
knowledge representation; social software systems; machine learning<br />
Teaching and Learning Methods and Adequate Assessment of Performance: The module<br />
is organized along lectures, assignments, and hands-on exercises (alone or in groups).<br />
When appropriate, tools are provided.<br />
Courses of Module:<br />
3.0/2.0 VO Knowledge Management<br />
3.0/2.0 UE Knowledge Managment<br />
SBI/KM2 - Information Extraction and Integration<br />
ECTS-Credits: 6.0<br />
Summary: This module deals with data extraction from the Web and integration of<br />
Web data into applications and processes. It comprises an overview about information<br />
extraction in general and covers in particular methods of Web querying and wrapper<br />
generation, as well as presenting wrapper languages, deep Web navigation traversal methods,<br />
and inductive, automated, and supervised approaches. Data extraction based on<br />
visual rendition, questions about robustness and adaptation, and further algorithmical<br />
and technical aspects are covered. Furthermore, a special focus of this module is how<br />
Web extraction and integration topics are addressed by state-of-the-art libraries, tools,<br />
and frameworks and used in real-life scenarios. Special emphasis is given to Web data<br />
cleansing, integration of Web data into competitive intelligence scenarios, mashups, web<br />
application testing, web process integration, and using extraction and document understanding<br />
technologies for enabling web accessibility. The course comprises both a lecture<br />
and an exercise part. The lecture part is primarily intended to teach about methodologies<br />
as well as to illustrate concepts from practice including system live demonstrations.<br />
The goal of the exercises is to strengthen the knowledge of the participants, especially<br />
including practical usage of tools in the area of web data extraction.<br />
Learning Outcomes:<br />
Knowledge:<br />
59