| Authors | Iman Behravan-Seyed Hamid Zahiri- Seyed Mohammad Razavi, Roberto Trasarti |
|---|---|
| Conference Title | international congress and exhibition of sciences and innovative technologies |
| Holding Date of Conference | 201809 |
| Presentation | SPEECH |
| Conference Level | International Conferences |
Abstract
Nowadays analyzing team sports using artificial intelligence algorithms has become one of
the most interesting topics for data scientists. On the other hand, it is really important for the
coaches and managers to analyze their own and opponents’ performance. So team sport
companies support data scientists to get good results based on the valuable knowledge
extracted by the data scientists from massive and unstructured datasets. Clustering, which is
the process of grouping data points in a dataset in to several clusters based on their
similarities, is one of the most important data mining and big data mining tools which has
been widely used in different fields. In this research a new automatic big data clustering
algorithm, based on a swarm intelligence method, is used to cluster a big dataset containing
centers of players’ performance in different soccer matches to extract the role of different
players in a soccer match. The proposed method consists of two phases. In the first phase
the algorithm tries to find proper number of clusters and in the second phase it tries to find
the position of the centroids. The dataset which is used in this research contains the center
of several players’ performance in about 93000 soccer matches which means that the dataset
has 93000 objects