{"id":"https://openalex.org/W2155097406","doi":"https://doi.org/10.1109/icsmc.2007.4414133","title":"A data-dependent distance measure for transductive instance-based learning","display_name":"A data-dependent distance measure for transductive instance-based learning","publication_year":2007,"publication_date":"2007-10-01","ids":{"openalex":"https://openalex.org/W2155097406","doi":"https://doi.org/10.1109/icsmc.2007.4414133","mag":"2155097406"},"language":"en","primary_location":{"id":"doi:10.1109/icsmc.2007.4414133","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2007.4414133","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Conference on Systems, Man and Cybernetics","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/A5010050355","display_name":"Jared Lundell","orcid":null},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jared Lundell","raw_affiliation_strings":["Department of Computer Science, Brigham Young University, Provo, UT, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Brigham Young University, Provo, UT, USA","institution_ids":["https://openalex.org/I100005738"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064318273","display_name":"Dan Ventura","orcid":"https://orcid.org/0000-0002-3111-2238"},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dan Ventura","raw_affiliation_strings":["Department of Computer Science, Brigham Young University, Provo, UT, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Brigham Young University, Provo, UT, USA","institution_ids":["https://openalex.org/I100005738"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5010050355"],"corresponding_institution_ids":["https://openalex.org/I100005738"],"apc_list":null,"apc_paid":null,"fwci":0.4836,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.77344173,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"14","issue":null,"first_page":"2825","last_page":"2830"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9886000156402588,"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/T10320","display_name":"Neural Networks and Applications","score":0.9886000156402588,"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/T10057","display_name":"Face and Expression Recognition","score":0.9846000075340271,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.983299970626831,"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/measure","display_name":"Measure (data warehouse)","score":0.7501178979873657},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7105855345726013},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.675263524055481},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6408371329307556},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6271668076515198},{"id":"https://openalex.org/keywords/distance-measures","display_name":"Distance measures","score":0.58624666929245},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5395895838737488},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4474126696586609},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2865067720413208}],"concepts":[{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.7501178979873657},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7105855345726013},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.675263524055481},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6408371329307556},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6271668076515198},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.58624666929245},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5395895838737488},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4474126696586609},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2865067720413208},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icsmc.2007.4414133","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2007.4414133","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Conference on Systems, Man and Cybernetics","raw_type":"proceedings-article"},{"id":"pmh:oai:scholarsarchive.byu.edu:facpub-1941","is_oa":false,"landing_page_url":"https://scholarsarchive.byu.edu/facpub/942","pdf_url":null,"source":{"id":"https://openalex.org/S4377196308","display_name":"ScholarsArchive  (Brigham Young University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I100005738","host_organization_name":"Brigham Young University","host_organization_lineage":["https://openalex.org/I100005738"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Faculty Publications","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.1021.2710","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1021.2710","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article%3D1941%26context%3Dfacpub","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W57680428","https://openalex.org/W1505873999","https://openalex.org/W2001141328","https://openalex.org/W2053186076","https://openalex.org/W2084812512","https://openalex.org/W2107008379","https://openalex.org/W2111557120","https://openalex.org/W2113592823","https://openalex.org/W2122837498","https://openalex.org/W2132820034","https://openalex.org/W2139956879","https://openalex.org/W2148603752","https://openalex.org/W2152010828","https://openalex.org/W2912210943","https://openalex.org/W2999575747","https://openalex.org/W6602375370","https://openalex.org/W6630275448","https://openalex.org/W6676132248","https://openalex.org/W6676772307","https://openalex.org/W6676834449","https://openalex.org/W6758700058"],"related_works":["https://openalex.org/W4255837520","https://openalex.org/W2387011115","https://openalex.org/W4234808182","https://openalex.org/W4255628145","https://openalex.org/W2382043075","https://openalex.org/W2809151339","https://openalex.org/W2808854221","https://openalex.org/W2216913934","https://openalex.org/W2360673138","https://openalex.org/W2393169369"],"abstract_inverted_index":{"We":[0],"consider":[1],"learning":[2,9,68],"in":[3,49],"a":[4,13,17],"transductive":[5],"setting":[6],"using":[7,21],"instance-based":[8,54],"(k-NN)":[10],"and":[11,56,71],"present":[12],"method":[14],"for":[15],"constructing":[16],"data-dependent":[18],"distance":[19,45],"\"metric\"":[20],"both":[22],"labeled":[23],"training":[24],"data":[25,31],"as":[26,28],"well":[27],"available":[29],"unlabeled":[30],"(that":[32],"is":[33,46,57],"to":[34,59,63],"be":[35],"classified":[36],"by":[37],"the":[38,50],"model).":[39],"This":[40],"new":[41],"data-driven":[42],"measure":[43],"of":[44,52],"empirically":[47],"studied":[48],"context":[51],"various":[53],"models":[55],"shown":[58],"reduce":[60],"error":[61],"(compared":[62],"traditional":[64],"models)":[65],"under":[66],"certain":[67],"conditions.":[69],"Generalizations":[70],"improvements":[72],"are":[73],"suggested.":[74]},"counts_by_year":[{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
