{"id":"https://openalex.org/W3080994088","doi":"https://doi.org/10.1145/3394486.3403151","title":"Correlation Networks for Extreme Multi-label Text Classification","display_name":"Correlation Networks for Extreme Multi-label Text Classification","publication_year":2020,"publication_date":"2020-08-20","ids":{"openalex":"https://openalex.org/W3080994088","doi":"https://doi.org/10.1145/3394486.3403151","mag":"3080994088"},"language":"en","primary_location":{"id":"doi:10.1145/3394486.3403151","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403151","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","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/A5048238468","display_name":"Guangxu Xun","orcid":"https://orcid.org/0000-0002-7657-4305"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Guangxu Xun","raw_affiliation_strings":["University of Virginia, Charlottesville, VA, USA"],"affiliations":[{"raw_affiliation_string":"University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021740848","display_name":"Kishlay Jha","orcid":"https://orcid.org/0000-0003-0826-445X"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kishlay Jha","raw_affiliation_strings":["University of Virginia, Charlottesville, VA, USA"],"affiliations":[{"raw_affiliation_string":"University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021218766","display_name":"Jianhui Sun","orcid":"https://orcid.org/0000-0003-0032-3646"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianhui Sun","raw_affiliation_strings":["University of Virginia, Charlottesville, VA, USA"],"affiliations":[{"raw_affiliation_string":"University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013588572","display_name":"Aidong Zhang","orcid":"https://orcid.org/0000-0001-9723-3246"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aidong Zhang","raw_affiliation_strings":["University of Virginia, Charlottesville, VA, USA"],"affiliations":[{"raw_affiliation_string":"University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5048238468"],"corresponding_institution_ids":["https://openalex.org/I51556381"],"apc_list":null,"apc_paid":null,"fwci":4.8289,"has_fulltext":false,"cited_by_count":58,"citation_normalized_percentile":{"value":0.95862769,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1074","last_page":"1082"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9998999834060669,"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":0.9998999834060669,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9972000122070312,"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/T10028","display_name":"Topic Modeling","score":0.9965999722480774,"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/computer-science","display_name":"Computer science","score":0.721322774887085},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6385568976402283},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5951226353645325},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5424962043762207},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5388135313987732},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5263941287994385},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.47255274653434753},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.44240617752075195},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4260685443878174},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38817334175109863},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1644519567489624},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08474019169807434}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.721322774887085},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6385568976402283},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5951226353645325},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5424962043762207},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5388135313987732},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5263941287994385},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.47255274653434753},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.44240617752075195},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4260685443878174},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38817334175109863},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1644519567489624},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08474019169807434},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394486.3403151","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403151","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.44999998807907104,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G5733619127","display_name":null,"funder_award_id":"IIS-1924928, IIS-1938167, OAC-1934600","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1781770377","https://openalex.org/W1834987204","https://openalex.org/W1924770834","https://openalex.org/W1981208470","https://openalex.org/W2061873838","https://openalex.org/W2064675550","https://openalex.org/W2068074736","https://openalex.org/W2099471712","https://openalex.org/W2176412452","https://openalex.org/W2194775991","https://openalex.org/W2250539671","https://openalex.org/W2362855512","https://openalex.org/W2428528690","https://openalex.org/W2520348554","https://openalex.org/W2739996966","https://openalex.org/W2740139069","https://openalex.org/W2743021690","https://openalex.org/W2744007523","https://openalex.org/W2744136723","https://openalex.org/W2788125153","https://openalex.org/W2792764867","https://openalex.org/W2920882081","https://openalex.org/W2949888546","https://openalex.org/W2954433047","https://openalex.org/W2963403868","https://openalex.org/W2964308564","https://openalex.org/W6691431627"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2358755282","https://openalex.org/W2625833328","https://openalex.org/W1533177136","https://openalex.org/W4380994516","https://openalex.org/W2251519152"],"abstract_inverted_index":{"This":[0],"paper":[1],"develops":[2],"the":[3,9,17,27,71,89,143],"Correlation":[4],"Networks":[5],"(CorNet)":[6],"architecture":[7],"for":[8],"extreme":[10],"multi-label":[11],"text":[12,24],"classification":[13],"(XMTC)":[14],"task,":[15],"where":[16],"objective":[18],"is":[19,97],"to":[20,99],"tag":[21],"an":[22,34,84],"input":[23],"sequence":[25],"with":[26,107,123],"most":[28],"relevant":[29],"subset":[30],"of":[31,92,150],"labels":[32],"from":[33],"extremely":[35],"large":[36],"label":[37,101,105,113],"set.":[38],"XMTC":[39,63,68,125,146],"can":[40,119,138],"be":[41,120],"found":[42],"in":[43,62,148],"many":[44],"real-world":[45],"applications,":[46],"such":[47],"as":[48],"document":[49],"tagging":[50],"and":[51,110,127,153,158],"product":[52],"annotation.":[53],"Recently,":[54],"deep":[55,67,94,124,145],"learning":[56],"models":[57,69,126,147,157],"have":[58],"achieved":[59],"outstanding":[60],"performances":[61],"tasks.":[64],"However,":[65],"these":[66],"ignore":[70],"useful":[72],"correlation":[73,108],"information":[74],"among":[75],"different":[76,131],"labels.":[77],"CorNet":[78,86,118,137],"addresses":[79],"this":[80],"limitation":[81],"by":[82],"adding":[83],"extra":[85],"module":[87],"at":[88],"prediction":[90],"layer":[91],"a":[93],"model,":[95],"which":[96],"able":[98],"learn":[100],"correlations,":[102],"enhance":[103],"raw":[104],"predictions":[106],"knowledge":[109],"output":[111],"augmented":[112],"predictions.":[114],"We":[115,133],"show":[116],"that":[117,136],"easily":[121],"integrated":[122],"generalize":[128],"effectively":[129],"across":[130],"datasets.":[132],"further":[134],"demonstrate":[135],"bring":[139],"significant":[140],"improvements":[141],"over":[142],"existing":[144],"terms":[149],"both":[151],"performance":[152],"convergence":[154],"rate.":[155],"The":[156],"datasets":[159],"are":[160],"available":[161],"at:":[162],"https://github.com/XunGuangxu/CorNet.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":8}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}