{"id":"https://openalex.org/W1499944261","doi":"https://doi.org/10.1109/icci-cc.2015.7259416","title":"Correlation-based pruning of dependent binary relevance models for Multi-label classification","display_name":"Correlation-based pruning of dependent binary relevance models for Multi-label classification","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W1499944261","doi":"https://doi.org/10.1109/icci-cc.2015.7259416","mag":"1499944261"},"language":"en","primary_location":{"id":"doi:10.1109/icci-cc.2015.7259416","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icci-cc.2015.7259416","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","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/A5030903526","display_name":"Yahong Zhang","orcid":"https://orcid.org/0000-0003-1148-949X"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]},{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yahong Zhang","raw_affiliation_strings":["Computer Science and Technology, Beijing University of Technology, Beijing, China","Computer Science and Technology, Beijing University of Technology, China"],"affiliations":[{"raw_affiliation_string":"Computer Science and Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I92403157","https://openalex.org/I37796252"]},{"raw_affiliation_string":"Computer Science and Technology, Beijing University of Technology, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101457814","display_name":"Yujian Li","orcid":"https://orcid.org/0000-0002-4991-6461"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]},{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujian Li","raw_affiliation_strings":["Computer Science and Technology, Beijing University of Technology, Beijing, China","Computer Science and Technology, Beijing University of Technology, China"],"affiliations":[{"raw_affiliation_string":"Computer Science and Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I92403157","https://openalex.org/I37796252"]},{"raw_affiliation_string":"Computer Science and Technology, Beijing University of Technology, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058443202","display_name":"Zhi Cai","orcid":"https://orcid.org/0000-0001-6732-6855"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]},{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Cai","raw_affiliation_strings":["Computer Science and Technology, Beijing University of Technology, Beijing, China","Computer Science and Technology, Beijing University of Technology, China"],"affiliations":[{"raw_affiliation_string":"Computer Science and Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I92403157","https://openalex.org/I37796252"]},{"raw_affiliation_string":"Computer Science and Technology, Beijing University of Technology, China","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5030903526"],"corresponding_institution_ids":["https://openalex.org/I37796252","https://openalex.org/I92403157"],"apc_list":null,"apc_paid":null,"fwci":0.4466,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.75531741,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"399","last_page":"404"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9998000264167786,"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":0.9998000264167786,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9922999739646912,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9889000058174133,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.8307110667228699},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7109165191650391},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.6534833312034607},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6500627398490906},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6370455622673035},{"id":"https://openalex.org/keywords/chaining","display_name":"Chaining","score":0.5618941187858582},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5204172730445862},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.49351346492767334},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47390878200531006},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40868741273880005},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3793361783027649},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3333953320980072},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2659972310066223}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.8307110667228699},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7109165191650391},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.6534833312034607},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6500627398490906},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6370455622673035},{"id":"https://openalex.org/C49020025","wikidata":"https://www.wikidata.org/wiki/Q1059099","display_name":"Chaining","level":2,"score":0.5618941187858582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5204172730445862},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.49351346492767334},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47390878200531006},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40868741273880005},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3793361783027649},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3333953320980072},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2659972310066223},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icci-cc.2015.7259416","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icci-cc.2015.7259416","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","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":19,"referenced_works":["https://openalex.org/W66588809","https://openalex.org/W1570448133","https://openalex.org/W1603920809","https://openalex.org/W1956267735","https://openalex.org/W1986159170","https://openalex.org/W1999954155","https://openalex.org/W2011972438","https://openalex.org/W2084465406","https://openalex.org/W2116373735","https://openalex.org/W2137107481","https://openalex.org/W2146241755","https://openalex.org/W2152052718","https://openalex.org/W2164898213","https://openalex.org/W2182822465","https://openalex.org/W3008214279","https://openalex.org/W6636209487","https://openalex.org/W6640791958","https://openalex.org/W6680483772","https://openalex.org/W6686272741"],"related_works":["https://openalex.org/W2139508594","https://openalex.org/W1995270367","https://openalex.org/W4387627836","https://openalex.org/W2767696758","https://openalex.org/W2107793209","https://openalex.org/W2041767423","https://openalex.org/W2378211422","https://openalex.org/W3028301851","https://openalex.org/W2901315987","https://openalex.org/W4200061056"],"abstract_inverted_index":{"Binary":[0],"relevance":[1,54],"(BR),":[2],"a":[3,10,61],"basic":[4],"Multi-label":[5],"classification":[6],"(MLC)":[7],"method,":[8],"learns":[9],"single":[11],"binary":[12,53],"model":[13],"for":[14,41,64,81],"each":[15],"different":[16],"label":[17],"without":[18],"considering":[19],"the":[20,32,38,68,95,105,112],"dependences":[21,33],"among":[22,34,79],"rest":[23],"of":[24,108],"labels.":[25,84],"Many":[26],"chaining":[27],"and":[28,94,110],"stacking":[29],"techniques":[30],"exploit":[31],"labels":[35,80],"to":[36,75],"improve":[37,111],"predictive":[39,113],"accuracy":[40],"MLC.":[42],"Using":[43],"these":[44],"two":[45],"techniques,":[46],"BR":[47],"has":[48,72],"been":[49,73],"promoted":[50],"as":[51],"dependent":[52],"(DBR).":[55],"In":[56],"this":[57],"paper":[58],"we":[59],"propose":[60],"pruning":[62,88,101],"method":[63],"DBR,":[65],"in":[66],"which":[67],"Phi":[69],"coefficient":[70],"function":[71],"employed":[74],"estimate":[76],"correlation":[77],"degrees":[78],"removing":[82],"irrelevant":[83],"We":[85],"conducted":[86],"our":[87,100],"algorithm":[89],"on":[90],"benchmark":[91],"multi-label":[92],"datasets,":[93],"experimental":[96],"results":[97],"show":[98],"that":[99],"approach":[102],"can":[103],"reduce":[104],"computational":[106],"cost":[107],"DBR":[109],"performance":[114],"generally.":[115]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}