National Repository of Grey Literature 4 records found  Search took 0.01 seconds. 
Business rule learning using data mining of GUHA association rules
Vojíř, Stanislav ; Strossa, Petr (advisor) ; Pour, Jan (referee) ; Kouba, Zdeněk (referee) ; Gregor, Jiří (referee)
In the currently highly competitive environment, the information systems of the businesses should not only effectively support the existing business processes, but also have to be dynamically adaptable to the changes in the environment. There are increasing efforts at separation of the application and the business logic in the information system. One of the appropriate instruments for this separation is the business rule approach. Business rules are simple, understandable rules. They can be used for the knowledge externalization and sharing also as for the active control and decisions within the business processes. Although the business rule approach is used for almost 20 years, the various specifications and practical applications of business rules are still a goal of the active research. The disadvantage of the business rule approach is great demands on obtaining of the rules. There has to be a domain expert, who is able to manually write them. One of the problems addressed by the current research is the possibility of (semi)automatic acquisition of business rules from the different resources - unstructured documents, historical data etc. This dissertation thesis addresses the problem of acquisition (learning) of business rules from the historical data of the company. The main objective of this thesis is to design and validate a method for (semi)automatic learning of business rules using the data mining of association rules. Association rule are a known data mining method for discovering of interesting relations hidden in the data. Association rules are comprehensible and explainable. The comprehensibility of association rules is suitable for the use of them for learning of business rules. For this purpose the user can use not only simple rules discovered using the algorithm Apriori or FP-Growth, but also more complex association rules discovered using the GUHA method. Within this thesis is used the procedure 4ft-Miner implemented in the data mining system LISp Miner. The first part of this thesis contains the description of the relevant topics from the research of business rules and association rules. Business rules is not a name of one specification of standard but rather a label of the approach to modelling of business logic. As part of the work there is defined a process of selection of the most appropriate specification of business rules for the selected practical use. Consequently, the author proposed three models of involving of data mining of association rules into business rule sets. These models contain also the definition of a model for the transformation of GUHA association rules in the business rules for the system JBoss Drools. For the possibility of learning of business rules using the data mining results from more than one data set, the author proposed a knowledge base. The knowledge base is suitable for the interconnection of business rules and data mining of association rules. From the perspective of business rules the knowledge base is a term dictionary. From the perspective of data mining the knowledge base contains some background knowledge for data preprocessing and preparation of classification models. The proposed models have been validated using practical implementations in the systems EasyMiner (in conjunction with JBoss Drools) and Erian. The thesis contains also a description of two model use cases based on real data from the field of marketing and the field of health insurance.
O problémech seřazení při řízení servisních operací
Lín, Václav ; Vomlel, Jiří (advisor) ; Jiroušek, Radim (referee) ; Kouba, Zdeněk (referee) ; Ottosen, Thorsten Jorgen (referee)
The subject of the thesis belongs to the field of operations management. We deal with sequencing problems arising when there are multiple repair operations available to fix a broken man-made system and the true cause of the system failure is uncertain. It is assumed that the system is formally described by a probabilistic model, and it is to be repaired by a sequence of troubleshooting operations designed to identify the cause of the malfunction and fix the system. The challenge is to find a course of repair which has minimal expected cost. We study several variants of the problem proposed in the literature. We analyze computational complexity of those variants, apply integer linear programming to one variant of the problem, and examine the relation to machine scheduling.
The practical marketing e-shop optimization
Hašková, Kateřina ; Sedláček, Jiří (advisor) ; Kouba, Zdeněk (referee)
Diploma thesis The practical marketing sales web optimization introduces to the reader the problematic of the Internet sales channel. The first chapter provides general aspects of internet business and introduces the concrete web, which is then used to validate the proposed procedures in the practical part of the Thesis. The chapter, entitled Initial analysis provides detailed analysis on a real Internet business, from technical, content and marketing perspective. The chapter Optimization applies and comments practical optimization steps in technical, content and marketing field. All the procedures proposed, and the result achieved are documented based on a verification using standard and recognized web analytics tool, web site traffic reporting tool and trades evaluation tools. The closing chapter Evaluation of optimization, evaluates the changes and extensions implemented and proposes additional both supplementary and strategic changes for the future.

Interested in being notified about new results for this query?
Subscribe to the RSS feed.