|
|
The real task of data mining
Trondin, Anton ; Berka, Petr (advisor) ; Chudán, David (referee)
Diploma thesis " The real role of knowledge mining " is divided into two major parts, the theoretical and the practical. The practical part describes the basic concepts of data mining, various methods and types of tasks used for knowledge discovery in databases and algorithms used in this area . Main focus is devoted to the CRISP -DM methodology and to various stages of knowledge discovery from databases. This methodology will be later used as the basis for practical part of the thesis while other less known methods used for data mining won`t be neglected. List of paid and free software which can be used for knowledge mining in databases is presented at the end of theoretical part. The second part of the thesis is focused on the practical step by step application of the CRISP -DM methodology, which contains real data from the field of mobile communications. Data mining task used in practical part is the behavioral prediction of mobile carrier customers. Supporting the practical part of the thesis, IBM SPSS Modeler was used as a main software for knowledge mining. Key words: data mining, knowledge disvocery in databases. Churm management, prediction, CRISP-DM.
|
|
|
Actual role of knowledge discovery in databases
Pešek, Jiří ; Berka, Petr (advisor) ; Máša, Petr (referee)
The thesis "Actual role of knowledge discovery in databases˝ is concerned with churn prediction in mobile telecommunications. The issue is based on real data of a telecommunication company and it covers all steps of data mining process. In accord with the methodology CRISP-DM, the work looks thouroughly at the following stages: business understanding, data understanding, data preparation, modeling, evaluation and deployment. As far as a system for knowledge discovery in databases is concerned, the tool IBM SPSS Modeler was selected. The introductory chapter of the theoretical part familiarises the reader with the issue of so called churn management, which comprises the given assignment; the basic concepts related to data mining are defined in the chapter as well. The attention is also given to the basic types of tasks of knowledge discovery of databasis and algorithms that are pertinent to the selected assignment (decision trees, regression, neural network, bayesian network and SVM). The methodology describing phases of knowledge discovery in databases is included in a separate chapter, wherein the methodology of CRIPS-DM is examined in greater detail, since it represents the foundation for the solution of our practical assignment. The conclusion of the theoretical part also observes comercial or freely available systems for knowledge discovery in databases.
|
|
|
Aplikace Business Intelligence v telekomunikačním sektoru
Višňová, Marika ; Novotný, Ota (advisor) ; Slánský, David (referee)
Čtenář bakalářské práce z kontextu pochopí logickou souvztažnost mezi děním na trhu telekomunikačního sektoru a potřebou orientace společnosti na zákazníka a tím i na Churn management. V práci jsou popsány principy a komponenty Business Intelligence a dolování dat, které tvoří technologický základ Churn managementu. V poslední kapitole, která je věnována samotnému Churn managementu, je ukázáno jak probíhá vytvoření prediktivního modelu dle metodiky CRISP-DM, což by mělo alespoň zprostředkovaně přiblížit Churn management v praxi.
|
guest ::
