Futbol Maç Anlatimlarindaki̇ Orta Açma Eylemleri̇ni̇n Büyük Di̇l Modelleri̇ Kullanilarak Otomati̇k Anali̇zi̇
Year: 2024
Type: dissertation
Abstract: In football, well-executed crosses have a significant impact, directly creating about 15% of scoring opportunities in the top leagues of England, Italy, and France. This thesis focuses on the development of a comprehensive dataset sourced from the in-depth analysis of football commentary extracted from the English Premier League matches spanning the 2022-2023 Football season. The main goal is to gather and organize key details related to crossing actions. This involves collecting diverse information, such as the outcome of each cross, identifying the team and the player making the cross, and evaluating the sentiment or qualitative aspects of the executed crosses with human annotators. In the second phase of the thesis, large language models are used and fine-tuned to automatically identify, extract, and describe instances of crossing actions, along with their related details, in the extensive football commentary from Premier League matches. The results indicate that the large language models are useful to reveal crossing actions successfully.
Author: Erkul, Anıl
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7110523668