As the role of soccer game analyst who analyzes soccer games and creates soccer wining strategies is emphasized, it is required to have high-level analysis beyond the procedural ones such as main event detection in the context of IT based broadcasting soccer game research community. In this paper, we propose a novel approach to generate the high-level in-depth analysis results via real-time text based soccer Webcast and text mining. Proposed method creates a metadata such as attribute, action and event, build index, and then generate available knowledges via text mining techniques such as association rule mining, event growth index, and pathfinder network analysis using Webcast and domain knowledges. We carried out a feasibility experiment on the proposed technique with the Webcast text about Spain team's 2010 World Cup games.
Jung et al. REF proposed a method of association rule mining, event growth index, and pathfinder network analysis to extract team performance-related knowledge by using text information provided by webcasts.
In-depth Analysis of Soccer Game via Webcast and Text Mining
The Journal of the Korea Contents Association
Engineering