{"id":"https://openalex.org/W4387848543","doi":"https://doi.org/10.1145/3583780.3615109","title":"WOT-Class: Weakly Supervised Open-world Text Classification","display_name":"WOT-Class: Weakly Supervised Open-world Text Classification","publication_year":2023,"publication_date":"2023-10-21","ids":{"openalex":"https://openalex.org/W4387848543","doi":"https://doi.org/10.1145/3583780.3615109"},"language":"en","primary_location":{"id":"doi:10.1145/3583780.3615109","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3583780.3615109","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3583780.3615109","source":null,"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 32nd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3583780.3615109","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101928623","display_name":"Tianle Wang","orcid":"https://orcid.org/0009-0003-7003-0264"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianle Wang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0003-7003-0264","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038338582","display_name":"Zihan Wang","orcid":"https://orcid.org/0000-0002-3147-4642"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zihan Wang","raw_affiliation_strings":["University of California, San Diego, La Jolla, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-3147-4642","affiliations":[{"raw_affiliation_string":"University of California, San Diego, La Jolla, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006765666","display_name":"Weitang Liu","orcid":"https://orcid.org/0000-0002-1740-5341"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weitang Liu","raw_affiliation_strings":["University of California, San Diego, La Jolla, CA, USA"],"raw_orcid":"https://orcid.org/0009-0001-4848-4054","affiliations":[{"raw_affiliation_string":"University of California, San Diego, La Jolla, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039500313","display_name":"Jingbo Shang","orcid":"https://orcid.org/0000-0002-7249-4404"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingbo Shang","raw_affiliation_strings":["University of California, San Diego, La Jolla, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-7249-4404","affiliations":[{"raw_affiliation_string":"University of California, San Diego, La Jolla, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2666","last_page":"2675"},"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/T10028","display_name":"Topic Modeling","score":0.9987000226974487,"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":0.9961000084877014,"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":0.7535704374313354},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.709748387336731},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6268607974052429},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6228770017623901},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6001155376434326},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5955632925033569},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5184473395347595},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.32051360607147217}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7535704374313354},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.709748387336731},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6268607974052429},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6228770017623901},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6001155376434326},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5955632925033569},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5184473395347595},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32051360607147217}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3583780.3615109","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3583780.3615109","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3583780.3615109","source":null,"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 32nd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3583780.3615109","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3583780.3615109","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3583780.3615109","source":null,"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 32nd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387848543.pdf","grobid_xml":"https://content.openalex.org/works/W4387848543.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W569478347","https://openalex.org/W1917989004","https://openalex.org/W2144211451","https://openalex.org/W2400705412","https://openalex.org/W2883725317","https://openalex.org/W2890931111","https://openalex.org/W2906971874","https://openalex.org/W2920292591","https://openalex.org/W2965989958","https://openalex.org/W2979826702","https://openalex.org/W3004119480","https://openalex.org/W3034588688","https://openalex.org/W3034640977","https://openalex.org/W3035458998","https://openalex.org/W3099045991","https://openalex.org/W3101606352","https://openalex.org/W3104770333","https://openalex.org/W3106109117","https://openalex.org/W3173777717","https://openalex.org/W3175562757","https://openalex.org/W4205868253","https://openalex.org/W4300672471","https://openalex.org/W6600020652"],"related_works":["https://openalex.org/W3125011624","https://openalex.org/W1508631387","https://openalex.org/W2370917603","https://openalex.org/W2952760143","https://openalex.org/W2017776670","https://openalex.org/W2347897961","https://openalex.org/W2340870721","https://openalex.org/W2358318464","https://openalex.org/W2979236518","https://openalex.org/W2119384858"],"abstract_inverted_index":{"State-of-the-art":[0],"weakly":[1,53],"supervised":[2,54],"text":[3,56,137,169,208],"classification":[4,87,170],"methods,":[5],"while":[6],"significantly":[7],"reduced":[8],"the":[9,15,20,73,100,112,157,199],"required":[10],"human":[11,33,205],"supervision,":[12],"still":[13],"requires":[14],"supervision":[16,59,105],"to":[17,28,138],"cover":[18],"all":[19,193],"classes":[21,71,81,154],"of":[22,52,102,134,202],"interest.":[23],"This":[24],"is":[25,60],"never":[26],"easy":[27],"meet":[29],"in":[30,82],"practice":[31],"when":[32],"explore":[34],"new,":[35],"large":[36,181],"corpora":[37],"without":[38],"complete":[39],"pictures.":[40],"In":[41],"this":[42],"paper,":[43],"we":[44],"work":[45],"on":[46,166],"a":[47,64,68,119,162,180],"novel":[48,120],"yet":[49],"important":[50],"problem":[51],"open-world":[55,86],"classification,":[57],"where":[58],"only":[61],"needed":[62],"for":[63,147,207],"few":[65,69],"examples":[66],"from":[67],"known":[70,78],"and":[72,79,106,143,150],"machine":[74],"should":[75],"handle":[76],"both":[77],"unknown":[80],"test":[83],"time.":[84],"General":[85],"has":[88],"been":[89],"studied":[90],"mostly":[91],"using":[92,156],"image":[93],"classification;":[94],"however,":[95],"existing":[96,190],"methods":[97],"typically":[98],"assume":[99],"availability":[101],"sufficient":[103],"known-class":[104],"strong":[107,126,176],"unknown-class":[108],"prior":[109],"knowledge":[110],"(e.g.,":[111],"number":[113],"and/or":[114],"data":[115],"distribution).":[116],"We":[117],"propose":[118],"framework":[121],"\u00f8ur":[122,174],"that":[123,173],"lifts":[124],"those":[125],"assumptions.":[127],"Specifically,":[128],"it":[129],"follows":[130],"an":[131],"iterative":[132],"process":[133],"(a)":[135],"clustering":[136],"new":[139],"classes,":[140],"(b)":[141],"mining":[142],"ranking":[144],"indicative":[145,159],"words":[146,160],"each":[148],"class,":[149],"(c)":[151],"merging":[152],"redundant":[153],"by":[155],"overlapped":[158],"as":[161],"bridge.":[163],"Extensive":[164],"experiments":[165],"7":[167],"popular":[168],"datasets":[171],"demonstrate":[172],"outperforms":[175],"baselines":[177],"consistently":[178],"with":[179],"margin,":[182],"attaining":[183],"23.33%":[184],"greater":[185],"average":[186],"absolute":[187],"macro-F1":[188],"over":[189],"approaches":[191],"across":[192],"datasets.":[194],"Such":[195],"competent":[196],"accuracy":[197],"illuminates":[198],"practical":[200],"potential":[201],"further":[203],"reducing":[204],"effort":[206],"classification.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}