| Title |
Automatinė šabloninių situacijų analizė sportinių įvykių sekose / |
| Translation of Title |
Automatical template situations analysis in sports events sequences. |
| Authors |
Suckel, Vitalij |
| Full Text |
|
| Pages |
53 |
| Keywords [eng] |
data mining ; sports events analysis ; spade algorithm ; sea system |
| Abstract [eng] |
Ways of analyzing vast amount of sports events data are examined in this paper. Data for analysis is stored in the system that was developed in process of writing this thesis. At the time of writing there are more than 400 thousand records about basketball events stored in the MySQL database that system uses for it's work. Therefore it is important to find the optimum algorithm and way to analyze this data. The main goal is to create, implement and test the algorithm which would provide ability to effectively examine data that is stored in the system. One of the most important task was to find a way to discover patterns in whole data set. The algorithm was implemented and some experiments were performed following the research. As a result of experiments most popular basketball game events patterns were discovered. Some data mining problems were highlighted and examined during research in order to develop the optimum algorithm for analysis. Descriptions and specifications of created tools and algorithms are presented in this paper along with actual SQL queries, examples, process and results of the experiments. |
| Type |
Master thesis |
| Language |
Lithuanian |
| Publication date |
2014 |
