Search from over 60,000 research works

Advanced Search

Data-mining chess databases

[thumbnail of 2010_ICGA_J_BHH_Data_Mining.pdf]
Preview
2010_ICGA_J_BHH_Data_Mining.pdf - Published Version (73kB) | Preview
Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Bleicher, E., Haworth, G. M. orcid id iconORCID: https://orcid.org/0000-0001-9896-1448 and van der Heijden, H. M. J. F. (2010) Data-mining chess databases. ICGA Journal, 33 (4). pp. 212-214. ISSN 1389-6911

Abstract/Summary

This is a report on the data-mining of two chess databases, the objective being to compare their sub-7-man content with perfect play as documented in Nalimov endgame tables. Van der Heijden’s ENDGAME STUDY DATABASE IV is a definitive collection of 76,132 studies in which White should have an essentially unique route to the stipulated goal. Chessbase’s BIG DATABASE 2010 holds some 4.5 million games. Insight gained into both database content and data-mining has led to some delightful surprises and created a further agenda.

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/17497
Item Type Article
Refereed Yes
Divisions Science
Uncontrolled Keywords castling, chess studies, cook, correctness, database, data-mining, DGT, dual, DTM, games, optimality, zugzwang
Publisher The International Computer Games Association
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar