{"id":"https://openalex.org/W4415421794","doi":"https://doi.org/10.15439/2025f1698","title":"A Stacking-Based Ensemble Approach for Predicting Chess Puzzle Difficulty","display_name":"A Stacking-Based Ensemble Approach for Predicting Chess Puzzle Difficulty","publication_year":2025,"publication_date":"2025-10-15","ids":{"openalex":"https://openalex.org/W4415421794","doi":"https://doi.org/10.15439/2025f1698"},"language":"en","primary_location":{"id":"doi:10.15439/2025f1698","is_oa":true,"landing_page_url":"https://doi.org/10.15439/2025f1698","pdf_url":"https://annals-csis.org/Volume_43/drp/pdf/1698.pdf","source":{"id":"https://openalex.org/S4220651875","display_name":"Annals of Computer Science and Information Systems","issn_l":"2300-5963","issn":["2300-5963"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":"https://openalex.org/P4310317484","host_organization_name":"Polskie Towarzystwo Informatyczne","host_organization_lineage":["https://openalex.org/P4310317484"],"host_organization_lineage_names":["Polskie Towarzystwo Informatyczne"],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annals of Computer Science and Information Systems","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://annals-csis.org/Volume_43/drp/pdf/1698.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022153151","display_name":"Alan Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I2800817003","display_name":"California Southern University","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alan Liang","raw_affiliation_strings":["University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern California","institution_ids":["https://openalex.org/I1174212","https://openalex.org/I2800817003"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Cenzhi Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210160355","display_name":"Fujian Petrochemical Group (China)","ror":"https://ror.org/04yep8s05","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210160355"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cenzhi Liu","raw_affiliation_strings":["Fuhua Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuhua Singapore","institution_ids":["https://openalex.org/I4210160355"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100437036","display_name":"Kai Wang","orcid":"https://orcid.org/0000-0002-6170-4744"},"institutions":[{"id":"https://openalex.org/I36788626","display_name":"California University of Pennsylvania","ror":"https://ror.org/01spssf70","country_code":"US","type":"education","lineage":["https://openalex.org/I36788626"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kai Wang","raw_affiliation_strings":["University of Pennsylvania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pennsylvania","institution_ids":["https://openalex.org/I36788626"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011690697","display_name":"Ethan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I192578771","display_name":"Rose\u2013Hulman Institute of Technology","ror":"https://ror.org/00mp6e841","country_code":"US","type":"education","lineage":["https://openalex.org/I192578771"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ethan Liu","raw_affiliation_strings":["Rose-Hulman Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rose-Hulman Institute of Technology","institution_ids":["https://openalex.org/I192578771"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":24.342,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.99315667,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"43","issue":null,"first_page":"819","last_page":"824"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9761999845504761,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9761999845504761,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.90420001745224,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3082999885082245},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.25760000944137573},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.25679999589920044},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.25200000405311584},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.23589999973773956}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5527999997138977},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5508999824523926},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3082999885082245},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28760001063346863},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.25760000944137573},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25200000405311584},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.23589999973773956},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.2328999936580658},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.22849999368190765}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.15439/2025f1698","is_oa":true,"landing_page_url":"https://doi.org/10.15439/2025f1698","pdf_url":"https://annals-csis.org/Volume_43/drp/pdf/1698.pdf","source":{"id":"https://openalex.org/S4220651875","display_name":"Annals of Computer Science and Information Systems","issn_l":"2300-5963","issn":["2300-5963"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":"https://openalex.org/P4310317484","host_organization_name":"Polskie Towarzystwo Informatyczne","host_organization_lineage":["https://openalex.org/P4310317484"],"host_organization_lineage_names":["Polskie Towarzystwo Informatyczne"],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annals of Computer Science and Information Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:doaj.org/article:115d63fd9e824d95883a8ec1cba6c876","is_oa":true,"landing_page_url":"https://doaj.org/article/115d63fd9e824d95883a8ec1cba6c876","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Annals of computer science and information systems, Vol 43, Pp 819-824 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.15439/2025f1698","is_oa":true,"landing_page_url":"https://doi.org/10.15439/2025f1698","pdf_url":"https://annals-csis.org/Volume_43/drp/pdf/1698.pdf","source":{"id":"https://openalex.org/S4220651875","display_name":"Annals of Computer Science and Information Systems","issn_l":"2300-5963","issn":["2300-5963"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":"https://openalex.org/P4310317484","host_organization_name":"Polskie Towarzystwo Informatyczne","host_organization_lineage":["https://openalex.org/P4310317484"],"host_organization_lineage_names":["Polskie Towarzystwo Informatyczne"],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annals of Computer Science and Information Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415421794.pdf","grobid_xml":"https://content.openalex.org/works/W4415421794.grobid-xml"},"referenced_works_count":4,"referenced_works":["https://openalex.org/W4406459881","https://openalex.org/W4406460071","https://openalex.org/W4406461958","https://openalex.org/W4415420677"],"related_works":[],"abstract_inverted_index":{"FedCSIS":[0,21],"2025":[1,22],"competition":[2],"is":[3,89],"to":[4,39,69,80,91],"predict":[5],"the":[6,20,93,108,138],"difficulty":[7,42],"of":[8,26,140],"chess":[9,148],"puzzles,":[10],"we":[11],"present":[12],"a":[13,50,75],"structured":[14,141],"multi-stage":[15],"regression":[16],"pipeline":[17],"developed":[18],"for":[19,98,145],"Challenge.The":[23],"approach":[24],"consists":[25],"three":[27],"stages:":[28],"(i)":[29],"four":[30],"Elo-banded":[31],"base":[32,55],"models":[33],"trained":[34],"on":[35],"separate":[36],"rating":[37],"ranges":[38],"capture":[40],"localized":[41],"semantics":[43],"and":[44,66,73,127],"mitigate":[45],"bias":[46],"in":[47,107],"imbalanced":[48],"datasets;(ii)":[49],"feature-level":[51],"stacking":[52],"ensemble":[53],"combining":[54],"predictions":[56],"with":[57,124],"structural":[58,125],"attributes,":[59],"such":[60],"as":[61],"success":[62],"probabilities,":[63],"failure":[64],"distributions,":[65],"solution":[67],"length,":[68],"enhance":[70],"cross-band":[71],"generalization;":[72],"(iii)":[74],"lightweight":[76],"post-hoc":[77],"residual":[78],"correction":[79],"reduce":[81],"systematic":[82],"prediction":[83],"biases.Additionally,":[84],"an":[85],"uncertaintyaware":[86],"mask-based":[87],"evaluation":[88],"introduced":[90],"identify":[92],"10%":[94],"most":[95],"challenging":[96],"puzzles":[97],"extended":[99],"scoring.Our":[100],"method":[101],"achieved":[102],"competitive":[103],"results,":[104],"ranking":[105],"7th":[106],"final":[109],"leaderboard,":[110],"while":[111],"maintaining":[112],"low":[113],"computational":[114],"cost.These":[115],"findings":[116],"demonstrate":[117],"that":[118],"lightweight,":[119],"interpretable":[120],"models,":[121],"when":[122],"combined":[123],"reasoning":[126],"uncertainty":[128],"estimation,":[129],"can":[130],"rival":[131],"more":[132],"complex":[133],"deep-learning":[134],"approaches.This":[135],"study":[136],"highlights":[137],"potential":[139],"machine":[142],"learning":[143],"pipelines":[144],"scalable,":[146],"human-centric":[147],"puzzle":[149],"analytics.":[150]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-24T07:32:12.397491","created_date":"2025-10-24T00:00:00"}
