{"id":"https://openalex.org/W7166147249","doi":"https://doi.org/10.1002/cpe.70815","title":"A Novel Conviction\u2010Driven Meta\u2010Learning Framework for Label\u2010Dependent Multi\u2010Label Classification","display_name":"A Novel Conviction\u2010Driven Meta\u2010Learning Framework for Label\u2010Dependent Multi\u2010Label Classification","publication_year":2026,"publication_date":"2026-06-26","ids":{"openalex":"https://openalex.org/W7166147249","doi":"https://doi.org/10.1002/cpe.70815"},"language":"en","primary_location":{"id":"doi:10.1002/cpe.70815","doi":"https://doi.org/10.1002/cpe.70815","is_oa":false,"landing_page_url":"https://doi.org/10.1002/cpe.70815","pdf_url":null,"source":{"id":"https://openalex.org/S11065456","display_name":"Concurrency and Computation Practice and Experience","issn_l":"1532-0626","issn":["1532-0626","1532-0634"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","ccf-c","cwts-core","dongbi-d","jufo-1","norway-1","poland-100","russia-white-list-2"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Concurrency and Computation: Practice and Experience","raw_type":"journal-article"},"volume":null,"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/A5058029454","display_name":"Puneet Himthani","orcid":"https://orcid.org/0000-0001-8966-8880","observed_orcids":["https://orcid.org/0000-0001-8966-8880"]},"institutions":[{"id":"https://openalex.org/I91277730","display_name":"Maulana Azad National Institute of Technology","ror":"https://ror.org/026vtd268","country_code":"IN","type":"education","lineage":["https://openalex.org/I91277730"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Puneet Himthani","raw_affiliation_strings":["Department of Computer Science and Engineering Maulana Azad National Institute of Technology  Bhopal Madhya Pradesh India"],"raw_orcid":"https://orcid.org/0000-0001-8966-8880","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering Maulana Azad National Institute of Technology  Bhopal Madhya Pradesh India","institution_ids":["https://openalex.org/I91277730"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078079341","display_name":"Meenu Chawla","orcid":"https://orcid.org/0000-0001-7832-8346","observed_orcids":["https://orcid.org/0000-0001-7832-8346"]},"institutions":[{"id":"https://openalex.org/I91277730","display_name":"Maulana Azad National Institute of Technology","ror":"https://ror.org/026vtd268","country_code":"IN","type":"education","lineage":["https://openalex.org/I91277730"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Meenu Chawla","raw_affiliation_strings":["Department of Computer Science and Engineering Maulana Azad National Institute of Technology  Bhopal Madhya Pradesh India"],"raw_orcid":"https://orcid.org/0000-0001-7832-8346","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering Maulana Azad National Institute of Technology  Bhopal Madhya Pradesh India","institution_ids":["https://openalex.org/I91277730"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038650263","display_name":"Namita Tiwari","orcid":"https://orcid.org/0000-0001-6355-9459","observed_orcids":["https://orcid.org/0000-0001-6355-9459"]},"institutions":[{"id":"https://openalex.org/I91277730","display_name":"Maulana Azad National Institute of Technology","ror":"https://ror.org/026vtd268","country_code":"IN","type":"education","lineage":["https://openalex.org/I91277730"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Namita Tiwari","raw_affiliation_strings":["Department of Computer Science and Engineering Maulana Azad National Institute of Technology  Bhopal Madhya Pradesh India"],"raw_orcid":"https://orcid.org/0000-0001-6355-9459","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering Maulana Azad National Institute of Technology  Bhopal Madhya Pradesh India","institution_ids":["https://openalex.org/I91277730"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5058029454"],"corresponding_institution_ids":["https://openalex.org/I91277730"],"apc_list":{"value":5140,"currency":"USD","value_usd":5140},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.46841039,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"38","issue":"13","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9980000257492065,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9980000257492065,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.0005000000237487257,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":9.999999747378752e-05,"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/multi-label-classification","display_name":"multi-label classification","score":0.9990000128746033},{"id":"https://openalex.org/keywords/stacking-ensemble","display_name":"stacking ensemble","score":0.7919999957084656},{"id":"https://openalex.org/keywords/meta-learning","display_name":"meta-learning","score":0.8830000162124634},{"id":"https://openalex.org/keywords/label-selection","display_name":"label selection","score":0.5070000290870667},{"id":"https://openalex.org/keywords/meta-features","display_name":"meta-features","score":0.8450000286102295}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.859499990940094},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7530999779701233},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6190999746322632},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6107000112533569},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6013000011444092},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5685999989509583},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5310999751091003},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5008999705314636},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.46160000562667847},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4442000091075897},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4034000039100647},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.36250001192092896},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.33480000495910645},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3328000009059906},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.33250001072883606},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.3319000005722046},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.31790000200271606},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.30469998717308044},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3001999855041504},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.27720001339912415},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.2599000036716461}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/cpe.70815","doi":"https://doi.org/10.1002/cpe.70815","is_oa":false,"landing_page_url":"https://doi.org/10.1002/cpe.70815","pdf_url":null,"source":{"id":"https://openalex.org/S11065456","display_name":"Concurrency and Computation Practice and Experience","issn_l":"1532-0626","issn":["1532-0626","1532-0634"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","ccf-c","cwts-core","dongbi-d","jufo-1","norway-1","poland-100","russia-white-list-2"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Concurrency and Computation: Practice and Experience","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7696545124053955}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1857789879","https://openalex.org/W1970696760","https://openalex.org/W1991527172","https://openalex.org/W2029517229","https://openalex.org/W2037108046","https://openalex.org/W2052684427","https://openalex.org/W2053463056","https://openalex.org/W2061554433","https://openalex.org/W2084465406","https://openalex.org/W2108638925","https://openalex.org/W2114315281","https://openalex.org/W2116373735","https://openalex.org/W2121325443","https://openalex.org/W2138290126","https://openalex.org/W2146241755","https://openalex.org/W2153677638","https://openalex.org/W2156935079","https://openalex.org/W2184222852","https://openalex.org/W2613794276","https://openalex.org/W2750406316","https://openalex.org/W2765940104","https://openalex.org/W2780112348","https://openalex.org/W2782959635","https://openalex.org/W2889149926","https://openalex.org/W2914876074","https://openalex.org/W2947746104","https://openalex.org/W2956380315","https://openalex.org/W2997794817","https://openalex.org/W3013251490","https://openalex.org/W3037520563","https://openalex.org/W3048192479","https://openalex.org/W3112713339","https://openalex.org/W3129918465","https://openalex.org/W3134948979","https://openalex.org/W3159499196","https://openalex.org/W4206778865","https://openalex.org/W4211256381","https://openalex.org/W4281772117","https://openalex.org/W4289342538","https://openalex.org/W4311770445","https://openalex.org/W4320497874","https://openalex.org/W4385067546","https://openalex.org/W4399423132","https://openalex.org/W4402965787","https://openalex.org/W4406947007"],"related_works":[],"abstract_inverted_index":{"ABSTRACT":[0],"Multi\u2010Label":[1,88],"Classification":[2,89],"(MLC),":[3],"a":[4,20,44,91,104,215],"common":[5],"problem":[6],"in":[7,76,145],"domains":[8],"like":[9],"biology,":[10],"semantic":[11],"scene":[12],"analysis,":[13],"and":[14,70,78,106,128,135,154,188,198,213,217],"text":[15],"classification,":[16],"involves":[17],"association":[18,68,100],"of":[19,30,38,110,122,131,167],"sample":[21],"with":[22],"more":[23],"than":[24],"one":[25],"class":[26,115,133],"label.":[27],"Effective":[28],"utilization":[29],"label":[31,51,207],"information":[32],"helps":[33],"improve":[34,150],"the":[35,59,151,199],"prediction":[36,152],"performance":[37,172,179],"multi\u2010label":[39,46,165,221],"classifiers.":[40,61],"Stacked":[41],"Generalization":[42],"is":[43,117,160,214],"two\u2010level":[45],"classification":[47],"technique":[48],"that":[49,94,149,184],"models":[50],"dependencies":[52,140],"by":[53],"feeding":[54],"base":[55,123],"classifier":[56],"predictions":[57,121],"into":[58,210],"meta":[60],"However,":[62],"existing":[63],"techniques":[64,176],"primarily":[65],"utilize":[66],"symmetric":[67],"measures":[69],"weight":[71],"all":[72],"labels":[73,116,134],"equally,":[74],"resulting":[75],"noise":[77],"ignoring":[79,136],"directional":[80,206],"relationships.":[81],"This":[82,143,202],"work":[83,203],"proposes":[84],"Conviction\u2010based":[85],"Stacking":[86,211],"for":[87,220],"(ConvST),":[90],"novel":[92,216],"framework":[93,159,219],"uses":[95],"conviction,":[96],"an":[97],"asymmetric,":[98],"rule\u2010based":[99],"measure":[101],"to":[102],"determine":[103],"label\u2010specific":[105],"directionally":[107],"relevant":[108,132],"subset":[109],"meta\u2010level":[111],"inputs.":[112],"Conviction":[113],"between":[114],"computed":[118],"based":[119],"on":[120,162],"classifiers;":[124],"thus,":[125,194],"enabling":[126],"dynamic":[127],"model\u2010aware":[129],"selection":[130],"weak":[137],"or":[138],"redundant":[139],"during":[141],"meta\u2010learning.":[142],"results":[144],"compact,":[146],"discriminative":[147],"meta\u2010features":[148],"efficiency":[153],"generalization":[155],"performance.":[156],"The":[157],"proposed":[158],"validated":[161],"16":[163],"benchmark":[164],"datasets":[166],"varying":[168],"domains,":[169],"comparing":[170],"its":[171,196],"against":[173,191],"eight":[174],"state\u2010of\u2010the\u2010art":[175],"across":[177],"13":[178],"measures.":[180],"Statistical":[181],"tests":[182],"demonstrate":[183],"ConvST":[185],"achieves":[186],"consistent":[187],"significant":[189],"improvements":[190],"most":[192],"techniques;":[193],"confirming":[195],"efficacy":[197],"theoretical":[200],"robustness.":[201],"integrates":[204],"conviction\u2010based,":[205],"dependency":[208],"modeling":[209],"MLC,":[212],"generalizable":[218],"classification.":[222]},"counts_by_year":[],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2026-06-27T00:00:00"}
