Study programmes / C-SE System engineering and informatics / IS/ICT
Course code:ISAC
Course title in language of instruction:IS/ICT
Course title in Czech:IS/ICT v AJ
Course title in English:IS/ICT
Mode of completion and number of credits:Exam (4 credits)
(1 ECTS credit = 28 hours of workload)
Mode of delivery/Timetabled classes:full-time, 1/2
(full-time, hours of lectures per week / hours of seminars per week)
Language of instruction:English
Level of course:master continuing
Semester:SS 2018/2019 - FBE
Name of lecturer:doc. Ing. František Dařena, Ph.D. (supervisor)
Prerequisites:Final Bachelor Exam
Aims of the course:The goal of the course is to gain knowledge in the field of knowledge discovery in text data and gaining practical skills in this field, everything in English.
Course contents:
1.Course introduction (allowance 1/0)
2.Literature review of a selected field (allowance 3/10)
a.Introducing some of the modern technologies
b.Writing technical papers in English
c.Preparation of presentations

3.Knowledge discovery in text data (allowance 7/14)
a.Introduction to text mining
b.Text data representation
c.Information retrieval

Learning outcomes and competences:
Generic competences:
-ability to communicate with professionals in different field of study
-ability to work in international context
-ability to work independently
-communication in second language
-skilled at utilizing and processing information

Specific competences:
-Students are able to discuss selected topics of IS/ICT in English.
-Students are able to synthesize recent knowledge from various domains of computer science
-Students are able to use foreign literary resources for their work

Type of course unit:required
Year of study:Not applicable - the subject could be chosen at anytime during the course of the programme.
Work placement:There is no compulsory work placement in the course unit.
Recommended study modules:none
Assessment methods:The course is finished by taking an oral exam. A necessary condition is preparation and presentation of a literature review from the field of knowledge discovery in text data and a realization of a practical knowledge discovery task.
Learning activities and study load (hours of study load)
Type of teaching methodDaily attendance
Direct teaching
     lecture14 h
     practice28 h
     public presentation (oral)10 h
     preparation of presentation28 h
     elaboration and execution of projects32 h
Total112 h

Basic reading list
  • FELDMAN, R. -- SANGER, J. The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data. Cambridge: Cambridge University Press, 2007. ISBN 978-0-521-83657-9.
  • MANNING, C D. -- RAGHAVAN, P. -- SCHÜTZE, H. Introduction to information retrieval. New York: Cambridge University Press, 2008. 482 p. ISBN 978-0-521-86571-5.
  • WEISS, S M. -- INDURKHYA, N. -- ZHANG, T. Text Mining: Predictive Methods for Analyzing Unstructured Information. New York: Springer, 2010. ISBN 978-1-4419-2996-9.
Recommended reading list
  • Data mining: practical machine learning tools and techniques. 3rd ed. Burlington, MA: Morgan Kaufmann, 629 p. [Morgan Kaufmann series in data management systems]. ISBN 978-0-12-374856-0.