Applying Data Mining to the Study of Joseki

Go is a strategic two player boardgame. Many studies have been done with regard to go in general, and to joseki, localized exchanges of stones that are considered fair for both players. We give an algorithm that finds and catalogues as many joseki as it can, as well as the global circumstances under which they are likely to be played, by analyzing a large number of professional go games. The method used applies several concepts, e.g., prefix trees, to extract knowledge from the vast amount of data.