{"id":"https://openalex.org/W2918387757","doi":"https://doi.org/10.1145/3290511.3290566","title":"Holonomic function of 2 parameter logistic model item response theory parameter estimation","display_name":"Holonomic function of 2 parameter logistic model item response theory parameter estimation","publication_year":2018,"publication_date":"2018-10-26","ids":{"openalex":"https://openalex.org/W2918387757","doi":"https://doi.org/10.1145/3290511.3290566","mag":"2918387757"},"language":"en","primary_location":{"id":"doi:10.1145/3290511.3290566","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3290511.3290566","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Conference on Education Technology and Computers","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/A5108366032","display_name":"Kazuhisa Noguchi","orcid":null},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuhisa Noguchi","raw_affiliation_strings":["Kyushu University, Fukuoka, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyushu University, Fukuoka, Japan","institution_ids":["https://openalex.org/I135598925"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090449160","display_name":"Eisuke Ito","orcid":"https://orcid.org/0000-0002-2045-2704"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Eisuke Ito","raw_affiliation_strings":["Kyushu University, Fukuoka, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyushu University, Fukuoka, Japan","institution_ids":["https://openalex.org/I135598925"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2413,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62077046,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"379","last_page":"382"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11716","display_name":"Random Matrices and Applications","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11716","display_name":"Random Matrices and Applications","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9336000084877014,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10792","display_name":"Matrix Theory and Algorithms","score":0.9085000157356262,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/holonomic","display_name":"Holonomic","score":0.8885663747787476},{"id":"https://openalex.org/keywords/item-response-theory","display_name":"Item response theory","score":0.7181851863861084},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.6404443979263306},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.6059324741363525},{"id":"https://openalex.org/keywords/likelihood-function","display_name":"Likelihood function","score":0.5663361549377441},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5141270756721497},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4607456922531128},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.4336821138858795},{"id":"https://openalex.org/keywords/logistic-function","display_name":"Logistic function","score":0.4276672601699829},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4221258759498596},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3671712279319763},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32261496782302856},{"id":"https://openalex.org/keywords/psychometrics","display_name":"Psychometrics","score":0.09802955389022827}],"concepts":[{"id":"https://openalex.org/C2777964439","wikidata":"https://www.wikidata.org/wiki/Q5884201","display_name":"Holonomic","level":2,"score":0.8885663747787476},{"id":"https://openalex.org/C19875794","wikidata":"https://www.wikidata.org/wiki/Q1207340","display_name":"Item response theory","level":3,"score":0.7181851863861084},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.6404443979263306},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.6059324741363525},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.5663361549377441},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5141270756721497},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4607456922531128},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.4336821138858795},{"id":"https://openalex.org/C180802074","wikidata":"https://www.wikidata.org/wiki/Q1052379","display_name":"Logistic function","level":2,"score":0.4276672601699829},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4221258759498596},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3671712279319763},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32261496782302856},{"id":"https://openalex.org/C171606756","wikidata":"https://www.wikidata.org/wiki/Q506132","display_name":"Psychometrics","level":2,"score":0.09802955389022827},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3290511.3290566","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3290511.3290566","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Conference on Education Technology and Computers","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":7,"referenced_works":["https://openalex.org/W571028990","https://openalex.org/W1547716543","https://openalex.org/W2076425730","https://openalex.org/W2107704778","https://openalex.org/W2157161039","https://openalex.org/W2963973710","https://openalex.org/W6616152328"],"related_works":["https://openalex.org/W2056060483","https://openalex.org/W2055233249","https://openalex.org/W2943251607","https://openalex.org/W2328467352","https://openalex.org/W2008854252","https://openalex.org/W1977225008","https://openalex.org/W2120595071","https://openalex.org/W3167036484","https://openalex.org/W1598553450","https://openalex.org/W2945972939"],"abstract_inverted_index":{"IRT":[0,42],"(Item":[1],"Response":[2],"Theory)":[3],"is":[4,23,58,64,81],"a":[5,35],"theory":[6],"for":[7,14,26],"scoring":[8],"of":[9,41],"tests,":[10],"and":[11,29],"it":[12],"used":[13],"some":[15],"test":[16],"systems":[17],"such":[18],"as":[19],"TOEFL.":[20],"IRT's":[21,69,78],"estimation":[22],"item":[24],"parameter":[25,40],"each":[27],"question,":[28],"examinee's":[30],"ability":[31],"parameter.":[32],"We":[33],"propose":[34],"new":[36],"method":[37],"to":[38],"estimate":[39],"using":[43],"the":[44],"Holonomic":[45,51,59,82],"Gradient":[46,52],"Method.":[47],"When":[48],"we":[49,54,75],"use":[50],"Method,":[53],"check":[55],"target":[56,62,77],"function":[57,63],"Function.":[60,71,83],"Our":[61],"2":[65],"Parameter":[66],"Logistic":[67],"Model":[68],"Likelihood":[70,79],"In":[72],"this":[73],"paper,":[74],"show":[76],"Function":[80]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}