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Avtomatsko prepoznavanje sorodnih šahovskih motivov v končnicah
ID MEDVED, ŽIGA (Author), ID Guid, Matej (Mentor) More about this mentor... This link opens in a new window

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Abstract
Iskanje podobnih šahovskih motivov v končnicah je problem, s katerim se pogosto srečujejo šahovski trenerji pri sestavi personaliziranega treninga za svoje učence. Iskanje takšnih motivov pogosto zahteva veliko časa, saj je pregledovanje in analiziranje celotnih partij zamuden proces. Pristop, ki smo ga uvedli, uporablja statične, dinamične in hevristične lastnosti šahovske pozicije, s pomočjo katerih smo tekstovno opisovali pozicije. Po generiranih opisih smo nato z metodami informacijskega poizvedovanja učinkovito iskali ter identificirali podobne pozicije. Metode smo nato še integrirali v strežniško arhitekturo, da smo izboljšali in olajšali uporabniško izkušnjo. Delovanje in učinkovitost sistema smo potrdili z eksperimentom v obliki ankete, ki so jo izpolnili šahisti.

Language:Slovenian
Keywords:pridobivanje informacij, šah, šahovske končnice, analiza besedil, šahovski motivi, umetna inteligenca, mikrostoritve
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FRI - Faculty of Computer and Information Science
Year:2024
PID:20.500.12556/RUL-153478 This link opens in a new window
COBISS.SI-ID:181871619 This link opens in a new window
Publication date in RUL:09.01.2024
Views:855
Downloads:87
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Secondary language

Language:English
Title:Automatic recognition of related chess motifs in endgames
Abstract:
Finding similar chess motifs in the endgames is a problem that chess coaches are often confronted with when designing personalised training for their students. Finding such motifs is often time-consuming, as reviewing and analysing entire games is a time-consuming process. The approach we have introduced uses static, dynamic and heuristic properties of a chess position to textually describe the positions. Following the generated descriptions, we then used information retrieval methods to efficiently search for and identify similar positions. The methods were then further integrated into the server architecture to improve and facilitate the user experience. We validated the performance and efficiency of the system through an experiment in the form of a survey completed by chess players.

Keywords:information retrieval, chess, chess endgames, text analysis, chess motifs, artificial intelligence, microservices

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