{"id":"https://openalex.org/W7204946155","doi":"https://doi.org/10.1145/3813822.3813885","title":"A Novel Imputation Method for Missing Values Using an RF-Based Approach","display_name":"A Novel Imputation Method for Missing Values Using an RF-Based Approach","publication_year":2026,"publication_date":"2026-03-20","ids":{"openalex":"https://openalex.org/W7204946155","doi":"https://doi.org/10.1145/3813822.3813885"},"language":"en","primary_location":{"id":"doi:10.1145/3813822.3813885","doi":"https://doi.org/10.1145/3813822.3813885","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3813822.3813885","pdf_url":null,"source":{"id":"https://openalex.org/S4306498704","display_name":"International Conference on Computer Information and Big Data Applications (CIBDA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 7th International Conference on Computer Information and Big Data Applications","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3813822.3813885","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100920818","display_name":"Xiaomei Feng","orcid":"https://orcid.org/0009-0004-6366-299X","observed_orcids":["https://orcid.org/0009-0004-6366-299X"]},"institutions":[{"id":"https://openalex.org/I49835588","display_name":"Macao Polytechnic University","ror":"https://ror.org/02sf5td35","country_code":"MO","type":"education","lineage":["https://openalex.org/I49835588"]}],"countries":["MO"],"is_corresponding":true,"raw_author_name":"Xiaomei Feng","raw_affiliation_strings":["Macao Polytechnic University, Macao, Macao"],"raw_orcid":"https://orcid.org/0009-0004-6366-299X","affiliations":[{"raw_affiliation_string":"Macao Polytechnic University, Macao, Macao","institution_ids":["https://openalex.org/I49835588"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100920818"],"corresponding_institution_ids":["https://openalex.org/I49835588"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"396","last_page":"400"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.6557999849319458,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.6557999849319458,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.1168999969959259,"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.051600001752376556,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/missing-data-imputation","display_name":"missing data imputation","score":0.9679999947547913},{"id":"https://openalex.org/keywords/missing-data","display_name":"missing data","score":0.8619999885559082},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.9739999771118164},{"id":"https://openalex.org/keywords/xgboost","display_name":"XGBoost","score":0.7179999947547913},{"id":"https://openalex.org/keywords/data-merging","display_name":"data merging","score":0.625},{"id":"https://openalex.org/keywords/model-accuracy-comparison","display_name":"model accuracy comparison","score":0.5270000100135803}],"concepts":[{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.9027000069618225},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.876800000667572},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6226999759674072},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5360999703407288},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38100001215934753},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.37709999084472656},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.35920000076293945},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2840999960899353},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3813822.3813885","doi":"https://doi.org/10.1145/3813822.3813885","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3813822.3813885","pdf_url":null,"source":{"id":"https://openalex.org/S4306498704","display_name":"International Conference on Computer Information and Big Data Applications (CIBDA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 7th International Conference on Computer Information and Big Data Applications","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3813822.3813885","doi":"https://doi.org/10.1145/3813822.3813885","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3813822.3813885","pdf_url":null,"source":{"id":"https://openalex.org/S4306498704","display_name":"International Conference on Computer Information and Big Data Applications (CIBDA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 7th International Conference on Computer Information and Big Data Applications","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2958026736","https://openalex.org/W3172701880","https://openalex.org/W4399745463","https://openalex.org/W4408159910"],"related_works":["https://openalex.org/W2735101699","https://openalex.org/W4297808664","https://openalex.org/W2961719033","https://openalex.org/W2581082906","https://openalex.org/W2887977587","https://openalex.org/W2772313640","https://openalex.org/W4394565199","https://openalex.org/W2146271290","https://openalex.org/W2991975888","https://openalex.org/W7127640412"],"abstract_inverted_index":{"Missing":[0],"data":[1],"has":[2,10],"been":[3],"a":[4],"prevalent":[5],"topic":[6],"for":[7],"decades":[8],"and":[9],"posed":[11],"challenges":[12],"since":[13],"the":[14,45,69,75,86,92],"advent":[15],"of":[16,71,85],"credit":[17],"cards.":[18],"This":[19],"paper":[20],"proposes":[21],"an":[22],"imputation":[23,63,97],"method":[24],"based":[25],"on":[26,35,74],"Random":[27],"Forest":[28],"method,":[29],"called":[30],"XGBRF.":[31],"Experiments":[32],"were":[33,48],"conducted":[34],"two":[36],"real-world":[37],"business":[38],"datasets,":[39],"where":[40],"missing":[41],"values":[42],"generated":[43],"from":[44],"merged":[46],"datasets":[47,78,88],"used":[49],"to":[50],"train":[51],"seven":[52],"popular":[53],"ML":[54],"models.":[55],"The":[56,65],"performance":[57],"was":[58],"compared":[59],"with":[60],"three":[61],"advanced":[62],"methods.":[64,98],"results":[66],"indicate":[67],"that":[68,84],"accuracy":[70,93],"models":[72],"trained":[73],"XGBRF":[76],"imputed":[77],"is":[79],"not":[80],"only":[81],"higher":[82],"than":[83],"original":[87],"but":[89],"also":[90],"exceeds":[91],"achieved":[94],"by":[95],"other":[96]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-09-02T00:00:00"}