| dc.contributor.advisor | Langseth, Helge | nb_NO |
| dc.contributor.author | Andresen, Thomas Rene | nb_NO |
| dc.contributor.author | Dubicki, Damian | nb_NO |
| dc.date.accessioned | 2014-12-19T13:40:52Z | |
| dc.date.available | 2014-12-19T13:40:52Z | |
| dc.date.created | 2013-11-06 | nb_NO |
| dc.date.issued | 2013 | nb_NO |
| dc.identifier | 662352 | nb_NO |
| dc.identifier | ntnudaim:10053 | nb_NO |
| dc.identifier.uri | http://hdl.handle.net/11250/253529 | |
| dc.description.abstract | The popularity of football has increased excessively since it originated, and inlater years, systems to predict football results have become a popular area ofresearch. Based on information found during a specialization project, the mostcommon way of predicting future matches is based on making observations of pre-vious match results. In this thesis we aim to develop and test a model that is ableto utilize more of the available data than what has been previously attempted.In addition we also aim to develop a framework that is able to automate most ofthe involved processes - from data mining to prediction to betting. | nb_NO |
| dc.language | eng | nb_NO |
| dc.publisher | Institutt for datateknikk og informasjonsvitenskap | nb_NO |
| dc.title | The Betting Machine | nb_NO |
| dc.type | Master thesis | nb_NO |
| dc.source.pagenumber | 74 | nb_NO |
| dc.contributor.department | Norges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskap | nb_NO |
