Automatic Recognition of Similar Chess Motifs

We present a novel method to find chess positions similar to a given query position from a collection of chess games. We consider not only the static similarity resulting from the arrangement of chess pieces, but also the dynamic similarity involving the recognition of chess motifs and the tactical, dynamic aspects of position similarity. By encoding chess tactical problems as text documents, we use information retrieval techniques to enable efficient approximate searches. We have also developed a method for automatically generating tactical puzzles from a collection of chess games. We have experimentally shown the importance of including both static and dynamic features for successful recognition of similar chess motifs. The experiments have clearly shown that dynamic similarity plays a very important role in the evaluation of the similarity of chess motifs by both the program and chess experts.