Thesis Details
Získávání znalostí pro modelování následných akcí
Knowledge discovery from databases is a complex issue involving integration, data preparation, data mining using machine learning methods and visualization of results. The thesis deals with the whole process of knowledge discovery, especially with the issue of data warehousing, where it offers the design and implementation of a specific data warehouse for the company ROI Hunter, a.s. In the field of data mining, the work focuses on the classification and forecasting of the advertising data available from the prepared data warehouse and, in particular, on the decision tree classification. When predicting the development of new ads, emphasis is put on the rationale for the prediction as well as the proposal to adjust the ad settings so that the prediction ends positively and, with a certain likelihood, the ads actually get better results.
Data mining, Knowledge discovery, Data warehouse, Data preprocessing, Classification, Prediction, Decision tree, Advertising, Advertisement.
Hrubý Martin, Ing., Ph.D. (DITS FIT BUT), člen
Janoušek Vladimír, doc. Ing., Ph.D. (DITS FIT BUT), člen
Jaroš Jiří, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Matyska Luděk, prof. RNDr., CSc. (FI MUNI), člen
Peringer Petr, Dr. Ing. (DITS FIT BUT), člen
@mastersthesis{FITMT20133, author = "Martin Veselovsk\'{y}", type = "Master's thesis", title = "Z\'{i}sk\'{a}v\'{a}n\'{i} znalost\'{i} pro modelov\'{a}n\'{i} n\'{a}sledn\'{y}ch akc\'{i}", school = "Brno University of Technology, Faculty of Information Technology", year = 2017, location = "Brno, CZ", language = "czech", url = "https://www.fit.vut.cz/study/thesis/20133/" }