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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Data Mining in the Field of English Football League Third Division's Betting Odds
 Faruzel, Jiří ; Berka, Petr (advisor) ; Šimůnek, Milan (referee)
Thesis "Data Mining in the Field of English Football League Third Division's Betting Odds" deals with data mining referring to acquiring knowledge from data. The main objective of this work is to develop data models for prediction of match results and to compare these predictions with a chosen strategy of betting. The selected betting strategy is based on betting single bets with odds belonging to chosen intervals, which generate a profit. These odds intervals were discovered by analyzing 2006-2009 football matches in a created simulator. On the basis of these odds ranges data models were constructed. Each data model contains a hypothesis which is generated by SD4ft procedure of LispMiner based on all football matches played in seasons 2001-2008. Developed data models are tested afterwards using 2006-2009 football matches data. Results show that all derived data models are profitable in all four seasons under consideration. More than half of them successfully predicted 2009 matches as well. The analysis showed that betting agencies offer mostly odds which make it almost impossible to be profitable while betting on matches according to their odds. In spite of this fact I identified some odds intervals with which you can success while betting single bets on home-team, draw or visitor-team with odds falling within these intervals. Association rules with reasonable confidence and support can generate high profitability. It is important to realize that there are no data models which guarantee a certain profit. Most of developed data models are not applicable in the real world, some of them can actually generate a loss. Nevertheless there are data models to be found that could generate a profit in the real world.
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Competitive Intelligence: A competitive environment analysis of PolyPLASTY s.r.o
 Faruzel, Jiří ; Sklenák, Vilém (advisor) ; Šišková, Petra (referee)
The goal of the presented work Competitive Intelligence: A competitive environment analysis of PolyPLASTY s.r.o. Company is to outline theoretical principals that are used for competitive environment analyses, to analyze the competitive environment of a company named PolyPLASTY s.r.o. and to design ontology for analysis of corporate competitive environment by using Topic Maps technology. A common contribution I would like to achieve by writing this paper is firstly to produce the competitive environment analysis for PolyPLASTY s.r.o. and to outline theoretical principles possible. Besides that, an annotated document and knowledge base essentials have been created. The knowledge base might me used for building a knowledge portal to monitor the competitive environment of PolyPLASTY Company systematically. This paper has been produced thanks to information gathered on an interview with Ing.Vlček and many other information resources. Seminar papers written by students of the University of Economics in Prague concerning competitive intelligence analysis for companies from Omni pack Cluster based on Porter's Five Forces method has been used a lot. The analysis has been produced as a structured document annotated by Topic Maps technology (in the structure used at the University of Economics) as well. The document also represents a knowledge base which can be used to build a knowledge portal for systematic monitoring of competitive environment of PolyPLASTY Company. The paper consists of two parts. The first one begins with Competitive Intelligence introduction. A plenty of theoretical principles that can be used for competitive intelligence analysis follow. Methods "Porter's five Forces Analysis" and STEEP (Social, Technological, Economic, Ecological and Political aspects) have been brought closer. At the end of the theoretical part the concept of Topic Maps have been described. The second part is concerned with application of mentioned methods in conditions of PolyPLASTY Company from Omni pack Cluster. The application part continues with a manager output describing acquired analysis results shortly. A description of created knowledge base concludes the second part. The annotated document as well as the knowledge base can be found on enclosed CD.
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