{"id":"https://openalex.org/W4394932682","doi":"https://doi.org/10.3390/bdcc8040043","title":"Knowledge-Enhanced Prompt Learning for Few-Shot Text Classification","display_name":"Knowledge-Enhanced Prompt Learning for Few-Shot Text Classification","publication_year":2024,"publication_date":"2024-04-18","ids":{"openalex":"https://openalex.org/W4394932682","doi":"https://doi.org/10.3390/bdcc8040043"},"language":"en","primary_location":{"id":"doi:10.3390/bdcc8040043","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc8040043","pdf_url":"https://www.mdpi.com/2504-2289/8/4/43/pdf?version=1713420846","source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-2289/8/4/43/pdf?version=1713420846","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101598712","display_name":"Jinshuo Liu","orcid":"https://orcid.org/0000-0002-2374-485X"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinshuo Liu","raw_affiliation_strings":["Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101339088","display_name":"Lu Yang","orcid":"https://orcid.org/0000-0002-6696-6399"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lu Yang","raw_affiliation_strings":["Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101339088"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":1.8253,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.8660858,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"8","issue":"4","first_page":"43","last_page":"43"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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/T10181","display_name":"Natural Language Processing Techniques","score":0.994700014591217,"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":0.9943000078201294,"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/shot","display_name":"Shot (pellet)","score":0.7201074957847595},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.559859037399292},{"id":"https://openalex.org/keywords/one-shot","display_name":"One shot","score":0.515070378780365},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45199233293533325},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3316723108291626},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.11965537071228027},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09206125140190125}],"concepts":[{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.7201074957847595},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.559859037399292},{"id":"https://openalex.org/C2992734406","wikidata":"https://www.wikidata.org/wiki/Q413267","display_name":"One shot","level":2,"score":0.515070378780365},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45199233293533325},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3316723108291626},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.11965537071228027},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09206125140190125},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/bdcc8040043","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc8040043","pdf_url":"https://www.mdpi.com/2504-2289/8/4/43/pdf?version=1713420846","source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:54744f46222e47f0967b7c187abc6569","is_oa":true,"landing_page_url":"https://doaj.org/article/54744f46222e47f0967b7c187abc6569","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Big Data and Cognitive Computing, Vol 8, Iss 4, p 43 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/bdcc8040043","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc8040043","pdf_url":"https://www.mdpi.com/2504-2289/8/4/43/pdf?version=1713420846","source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3415419065","display_name":null,"funder_award_id":"U193607","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4394932682.pdf"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W205829674","https://openalex.org/W1552847225","https://openalex.org/W2121678312","https://openalex.org/W2127426251","https://openalex.org/W2127795553","https://openalex.org/W2158028897","https://openalex.org/W2170240176","https://openalex.org/W2184957013","https://openalex.org/W2283196293","https://openalex.org/W2561529111","https://openalex.org/W2896457183","https://openalex.org/W2909137510","https://openalex.org/W2937423263","https://openalex.org/W2963748441","https://openalex.org/W2970986510","https://openalex.org/W3098266846","https://openalex.org/W3098267758","https://openalex.org/W3103433205","https://openalex.org/W3105625590","https://openalex.org/W3114459349","https://openalex.org/W3114916066","https://openalex.org/W3151929433","https://openalex.org/W3153427360","https://openalex.org/W3156012351","https://openalex.org/W3162305607","https://openalex.org/W3168811396","https://openalex.org/W3173777717","https://openalex.org/W3174770825","https://openalex.org/W3188542058","https://openalex.org/W3207553988","https://openalex.org/W4205991051","https://openalex.org/W4288089799","https://openalex.org/W4292779060","https://openalex.org/W4309811444","https://openalex.org/W4385965964","https://openalex.org/W4386187806","https://openalex.org/W6678830454","https://openalex.org/W6678846912","https://openalex.org/W6685053522","https://openalex.org/W6761783306","https://openalex.org/W6769627184","https://openalex.org/W6778883912"],"related_works":["https://openalex.org/W2497720472","https://openalex.org/W4292659306","https://openalex.org/W3044321615","https://openalex.org/W4294892107","https://openalex.org/W2806221744","https://openalex.org/W2326937258","https://openalex.org/W394267150","https://openalex.org/W2773965352","https://openalex.org/W2357748469","https://openalex.org/W2392917037"],"abstract_inverted_index":{"Classification":[0],"methods":[1],"based":[2,139],"on":[3,140,178],"fine-tuning":[4],"pre-trained":[5],"language":[6,60],"models":[7],"often":[8,75],"require":[9,76],"a":[10,53,58,104,113],"large":[11],"number":[12],"of":[13,41,188],"labeled":[14],"samples;":[15],"therefore,":[16],"few-shot":[17,32,179],"text":[18,33,54,180],"classification":[19,34,55,181],"has":[20,191],"attracted":[21],"considerable":[22],"attention.":[23],"Prompt":[24],"learning":[25],"is":[26,44,82,112],"an":[27,150],"effective":[28],"method":[29],"for":[30],"addressing":[31],"tasks":[35,182],"in":[36,90],"low-resource":[37],"settings.":[38],"The":[39],"essence":[40],"prompt":[42,66,107,115,123,125,137],"tuning":[43,108,116],"to":[45,143,154,171],"insert":[46,132],"tokens":[47,134],"into":[48,57,135],"the":[49,86,136,158,168,173,186],"input,":[50],"thereby":[51],"converting":[52],"task":[56],"masked":[59],"modeling":[61],"problem.":[62],"However,":[63],"constructing":[64],"appropriate":[65],"templates":[67],"and":[68,92,127,156],"verbalizers":[69],"remains":[70],"challenging,":[71],"as":[72],"manual":[73],"prompts":[74,81],"expert":[77],"knowledge,":[78],"while":[79],"auto-constructing":[80],"time-consuming.":[83],"In":[84],"addition,":[85],"extensive":[87,176],"knowledge":[88,106,165],"contained":[89],"entities":[91],"relations":[93],"should":[94],"not":[95],"be":[96],"ignored.":[97],"To":[98],"address":[99],"these":[100],"issues,":[101],"we":[102,131,148,162],"propose":[103],"structured":[105,164],"(SKPT)":[109],"method,":[110],"which":[111],"knowledge-enhanced":[114],"approach.":[117],"Specifically,":[118],"SKPT":[119],"includes":[120],"three":[121],"components:":[122],"template,":[124],"verbalizer,":[126],"training":[128,169],"strategies.":[129],"First,":[130],"virtual":[133],"template":[138],"open":[141],"triples":[142],"introduce":[144],"external":[145],"knowledge.":[146],"Second,":[147],"use":[149,163],"improved":[151],"knowledgeable":[152],"verbalizer":[153],"expand":[155],"filter":[157],"label":[159],"words.":[160],"Finally,":[161],"constraints":[166],"during":[167],"phase":[170],"optimize":[172],"model.":[174],"Through":[175],"experiments":[177],"with":[183],"different":[184],"settings,":[185],"effectiveness":[187],"our":[189],"model":[190],"been":[192],"demonstrated.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-01-01T23:40:50.289205","created_date":"2025-10-10T00:00:00"}