Chess Query Language
| Chess Query Language | |
|---|---|
| Basic data
|
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| Maintainer | Gady Costeff |
| developer | Gady Costeff and Lewis Stiller |
| Publishing year | 2003 |
| Current version | 5.1 (February 22, 2017) |
| operating system | Windows, Mac |
| category | Chess software |
| License | proprietary freeware |
| German speaking | No |
| http://gadycosteff.com/cql/ | |
Chess Query Language (CQL) is a language for querying specific situations in chess games or chess studies . The games or studies must be available in Portable Game Notation and are searched for the situation to be described in CQL. CQL is used, among other things, for the scientific evaluation of chess games.
Delimitation and Limitations
A related query system for chess positions is Query by Example (QBE). Each position in a game is hashed (usually using Zobrist hashing ) and stored in a hash table . To query a specific position, its hash is calculated and the matching results are returned from the database. This approach can also be applied efficiently to very large game collections.
The main disadvantage of this method is that it can only find exact hits. Even slightly different positions lead to a completely different hash value and are not found via QBE. CQL avoids this disadvantage by making an approximate search possible. A Boolean filter is used for this purpose, which precisely specifies the desired position. The query
(position [RQ]b2 bg8)
finds, for example, all positions with a white rook or a white queen on the b2 square and a black bishop on g8. However, this approach is considerably slower than hash-based searches with QBE, even with moderately large databases.
The Boolean nature of the query represents a further restriction: it can only return exact hits, but cannot weight them according to their similarity to a desired position.
Web links
- Homepage of the CQL
- Old CQL homepage ( Memento from March 3, 2016 in the Internet Archive )
- Tim Krabbés CHESS CURIOSITIES
Individual evidence
- ↑ Madeeh Al-Gedawy, Osman Hegazy: Enriching the Text Mining Capabilities by Transforming the Text Mining Domain to Chess Game Domain to Simulate Future Scenarios . In: International Journal of Computer Applications . Volume 45, No. 16, 2012, ISSN 0975-8887 , p. 48-58 ( online [PDF]).
- ↑ a b c Debasis Ganguly, Johannes Leveling, Gareth JF Jones: Retrieval of Similar Chess Positions . In: Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval (= SIGIR '14 ). 2014, ISBN 978-1-4503-2257-7 , pp. 687-696 , doi : 10.1145 / 2600428.2609605 .