{"id":"https://openalex.org/W4406461599","doi":"https://doi.org/10.1109/bigdata62323.2024.10825991","title":"Estimating the Puzzlingness of Chess Puzzles","display_name":"Estimating the Puzzlingness of Chess Puzzles","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406461599","doi":"https://doi.org/10.1109/bigdata62323.2024.10825991"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825991","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825991","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115905171","display_name":"Sebastian Bj\u00f6rkqvist","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Sebastian Bj\u00f6rkqvist","raw_affiliation_strings":["IPRally Technologies Oy,Helsinki,Finland"],"affiliations":[{"raw_affiliation_string":"IPRally Technologies Oy,Helsinki,Finland","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5115905171"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.2733,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.93273419,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"8370","last_page":"8376"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T12002","display_name":"Computability, Logic, AI Algorithms","score":0.9544000029563904,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9535999894142151,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6126883625984192},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.3208308815956116}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6126883625984192},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3208308815956116}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825991","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825991","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2342249984","https://openalex.org/W2747329762","https://openalex.org/W2912083425","https://openalex.org/W3033620876","https://openalex.org/W4295312788","https://openalex.org/W4389315178","https://openalex.org/W4399836594","https://openalex.org/W4403322259","https://openalex.org/W4403709777","https://openalex.org/W4403816328","https://openalex.org/W4406461958","https://openalex.org/W6638667902","https://openalex.org/W6691708969","https://openalex.org/W6739879593","https://openalex.org/W6745609711","https://openalex.org/W6747894552","https://openalex.org/W6757817989","https://openalex.org/W6869758107","https://openalex.org/W6872788215","https://openalex.org/W6873303801","https://openalex.org/W6874564148"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Solving":[0],"chess":[1,31,42,72,97],"puzzles,":[2],"which":[3],"require":[4],"finding":[5],"a":[6,13,20,25,41,65,110,137],"certain":[7],"sequence":[8,81],"of":[9,71,82,123],"moves":[10],"to":[11,52,114,136,143,153],"achieve":[12],"winning":[14],"position":[15,78],"(such":[16],"as":[17,100,134],"checkmate":[18],"or":[19],"significant":[21],"material":[22],"advantage),":[23],"is":[24,44],"commonly":[26],"used":[27],"method":[28,66],"for":[29,67],"improving":[30],"skills,":[32],"particularly":[33],"tactical":[34],"awareness.":[35],"Estimating":[36],"the":[37,39,50,69,76,80,117,129,145,154],"puzzlingness\u2014i.e.,":[38],"difficulty\u2014of":[40],"puzzle":[43,51,119],"challenging":[45],"and":[46,55,79,93,105],"typically":[47],"involves":[48],"showing":[49],"multiple":[53,87],"players":[54],"measuring":[56],"their":[57],"success":[58],"rate.":[59],"In":[60],"this":[61,124],"work,":[62],"we":[63],"present":[64],"predicting":[68],"difficulty":[70],"puzzles":[73],"using":[74],"only":[75],"initial":[77],"correct":[83],"moves.":[84],"We":[85,107],"generate":[86],"features,":[88,132],"including":[89],"both":[90],"hand-crafted":[91],"features":[92],"those":[94],"extracted":[95],"from":[96],"engines":[98],"such":[99],"Maia,":[101],"Leela":[102],"Chess":[103,162],"Zero,":[104],"Stockfish.":[106],"also":[108],"train":[109],"residual":[111],"neural":[112,125],"network":[113],"directly":[115],"predict":[116,144],"Glicko-2":[118,147],"rating.":[120,148],"The":[121],"output":[122],"network,":[126],"along":[127],"with":[128],"other":[130],"generated":[131],"serves":[133],"input":[135],"gradient":[138],"boosting":[139],"decision":[140],"tree":[141],"model":[142,150],"final":[146],"Our":[149],"was":[151],"applied":[152],"IEEE":[155],"BigData":[156],"2024":[157],"Cup":[158],"competition":[159],"on":[160],"Predicting":[161],"Puzzle":[163],"Difficulty,":[164],"where":[165],"it":[166],"achieved":[167],"third":[168],"place.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
