{"id":"https://openalex.org/W6888818814","doi":"https://doi.org/10.2312/eg2011/areas/017-024","title":"Learning How to Match Fresco Fragments","display_name":"Learning How to Match Fresco Fragments","publication_year":2011,"publication_date":"2011-01-01","ids":{"openalex":"https://openalex.org/W6888818814","doi":"https://doi.org/10.2312/eg2011/areas/017-024"},"language":"en","primary_location":{"id":"doi:10.2312/eg2011/areas/017-024","is_oa":true,"landing_page_url":"https://doi.org/10.2312/eg2011/areas/017-024","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"other","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.2312/eg2011/areas/017-024","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Funkhouser, T.","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Funkhouser, T.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Shin, H.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shin, H.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Toler-Franklin, C.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Toler-Franklin, C.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Casta\u00f1eda, A. Garc\u00eda","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Casta\u00f1eda, A. Garc\u00eda","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Brown, B.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brown, B.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Dobkin, D.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dobkin, D.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Rusinkiewicz, S.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rusinkiewicz, S.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Weyrich, T.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weyrich, T.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5263000130653381},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.4066999852657318},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.3871000111103058},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3711000084877014},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3675999939441681},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.36340001225471497}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6664000153541565},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5263000130653381},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5091000199317932},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42489999532699585},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.4066999852657318},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.3871000111103058},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3711000084877014},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3675999939441681},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.36340001225471497},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.35760000348091125},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.34619998931884766},{"id":"https://openalex.org/C75947009","wikidata":"https://www.wikidata.org/wiki/Q134194","display_name":"Fresco","level":3,"score":0.34529998898506165},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.34310001134872437},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.3278000056743622},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3174000084400177},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.27950000762939453}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2312/eg2011/areas/017-024","is_oa":true,"landing_page_url":"https://doi.org/10.2312/eg2011/areas/017-024","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.2312/eg2011/areas/017-024","is_oa":true,"landing_page_url":"https://doi.org/10.2312/eg2011/areas/017-024","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.8057117462158203}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"One":[0],"of":[1,8,18,44,46,102,118,188],"the":[2,25,91,100],"main":[3],"problems":[4],"faced":[5],"during":[6],"reconstruction":[7,191],"fractured":[9],"archaeological":[10],"artifacts":[11],"is":[12,96,151],"sorting":[13],"through":[14],"a":[15,42,66,85,94,155,186],"large":[16],"number":[17],"candidate":[19],"matches":[20,113,137,171],"between":[21],"fragments":[22],"to":[23,153,168],"find":[24],"relatively":[26],"few":[27,67],"that":[28,89,93,122,149,179],"are":[29],"correct.":[30],"Previous":[31],"computer":[32],"methods":[33],"for":[34,111],"this":[35,81,107,180],"task":[36],"provided":[37],"scoring":[38],"functions":[39],"based":[40,98,124,140],"on":[41,99,125,141,157],"variety":[43,187],"properties":[45,68,128,159],"potential":[47],"matches,":[48],"including":[49],"color":[50],"and":[51,71,164],"geometric":[52],"compatibility":[53],"across":[54],"fracture":[55],"surfaces.":[56],"However,":[57],"they":[58],"usually":[59],"consider":[60],"only":[61],"one":[62,161],"or":[63],"at":[64,69,134],"most":[65],"once,":[70],"therefore":[72],"provide":[73],"match":[74,95,127,158],"predictions":[75],"with":[76],"very":[77],"low":[78],"precision.":[79],"In":[80],"paper,":[82],"we":[83],"investigate":[84],"machine":[86,108],"learning":[87,109],"approach":[88,110,181],"computes":[90],"probability":[92],"correct":[97],"combination":[101],"many":[103,126],"features.":[104],"We":[105,177],"explore":[106],"ranking":[112,135],"in":[114,160,172,185],"three":[115],"different":[116],"sets":[117],"fresco":[119],"fragments,":[120],"finding":[121],"classifiers":[123],"can":[129],"be":[130,183],"significantly":[131],"more":[132],"effective":[133],"proposed":[136],"than":[138],"scores":[139],"any":[142],"single":[143],"property":[144],"alone.":[145],"Our":[146],"results":[147],"suggest":[148],"it":[150,167],"possible":[152],"train":[154],"classifier":[156],"data":[162,174],"set":[163,175],"then":[165],"use":[166],"rank":[169],"predicted":[170],"another":[173],"effectively.":[176],"believe":[178],"could":[182],"helpful":[184],"cultural":[189],"heritage":[190],"systems.":[192]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
