Summary of topics offered - Department of Informatics (FBE)
|Type of work:|
|Topic:||Mining and using context-specific knowledge hidden in text data|
State of topic:
approved (prof. Ing. Cyril Klimeš, CSc. - head of department)
Faculty of Business and Economics
|Supervising department:||Department of Informatics - FBE|
|Max. no. of students:||--|
Text documents are a potential source of knowledge useful for decision support across a range of business activities. In many areas, however, this data source is not given adequate attention or has a number of unsolved related issues. The dissertation will focus on mining knowledge relevant for a domain selected by the student (marketing research, access to foreign markets, improving products/services, decisions on investment strategy, analysis of public opinion, etc.). Mining knowledge will rely mainly on the methods of inductive machine learning, including supervised, unsupervised, on semi-supervised methods and their combinations. During the entire process suitable external information from the related problem domain will be used, often processed and included in the mining process automatically.
Limitations of the topic
To sign up for a topic it is necessary to fulfil one of the following restrictions
Restrictions by study
The table shows restrictions by study to which the student has to be enrolled in order to sign up for the given topic.
|D-SIA System Engineering and Informatics|