{"id":"https://openalex.org/W7127586857","doi":"https://doi.org/10.14569/ijacsa.2026.0170141","title":"A Few-Shot Semantic Meta-Learning Framework with CRF for Skill Entity Recognition in Open Innovation Ecosystems","display_name":"A Few-Shot Semantic Meta-Learning Framework with CRF for Skill Entity Recognition in Open Innovation Ecosystems","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7127586857","doi":"https://doi.org/10.14569/ijacsa.2026.0170141"},"language":"en","primary_location":{"id":"doi:10.14569/ijacsa.2026.0170141","doi":"https://doi.org/10.14569/ijacsa.2026.0170141","is_oa":true,"landing_page_url":"https://doi.org/10.14569/ijacsa.2026.0170141","pdf_url":"https://thesai.org/Downloads/Volume17No1/Paper_41-A_Few_Shot_Semantic_Meta_Learning_Framework.pdf","source":{"id":"https://openalex.org/S23629721","display_name":"International Journal of Advanced Computer Science and Applications","issn_l":"2156-5570","issn":["2156-5570","2158-107X"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","norway-1","poland-20","russia-white-list-3","vabb-shw"],"host_organization":"https://openalex.org/P4310311819","host_organization_name":"Science and Information Organization","host_organization_lineage":["https://openalex.org/P4310311819"],"host_organization_lineage_names":["Science and Information Organization"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Advanced Computer Science and Applications","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W7127586857"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://thesai.org/Downloads/Volume17No1/Paper_41-A_Few_Shot_Semantic_Meta_Learning_Framework.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121585564","display_name":"Nurchim","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210127958","display_name":"Universitas Dian Nuswantoro","ror":"https://ror.org/02csxcg02","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210127958"]},{"id":"https://openalex.org/I4405259982","display_name":"Universitas Duta Bangsa","ror":"https://ror.org/030zqsq57","country_code":"ID","type":"education","lineage":["https://openalex.org/I4405259982"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Nurchim -","raw_affiliation_strings":["Doctoral Program of Computer Science , Universitas Dian Nuswantoro , Semarang , Indonesia ,","Faculty of Computer Science , Universitas Duta Bangsa Surakarta , Surakarta , Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Doctoral Program of Computer Science , Universitas Dian Nuswantoro , Semarang , Indonesia ,","institution_ids":["https://openalex.org/I4210127958"]},{"raw_affiliation_string":"Faculty of Computer Science , Universitas Duta Bangsa Surakarta , Surakarta , Indonesia","institution_ids":["https://openalex.org/I4405259982"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082192553","display_name":"Muljono","orcid":"https://orcid.org/0000-0001-6059-3571","observed_orcids":["https://orcid.org/0000-0001-6059-3571"]},"institutions":[{"id":"https://openalex.org/I4210127958","display_name":"Universitas Dian Nuswantoro","ror":"https://ror.org/02csxcg02","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210127958"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Muljono -","raw_affiliation_strings":["Doctoral Program of Computer Science , Universitas Dian Nuswantoro , Semarang , Indonesia ,","Faculty of Computer Science , Universitas Dian Nuswantoro , Semarang , Indonesia ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Doctoral Program of Computer Science , Universitas Dian Nuswantoro , Semarang , Indonesia ,","institution_ids":["https://openalex.org/I4210127958"]},{"raw_affiliation_string":"Faculty of Computer Science , Universitas Dian Nuswantoro , Semarang , Indonesia ,","institution_ids":["https://openalex.org/I4210127958"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089820727","display_name":"Edi Noersasongko","orcid":"https://orcid.org/0009-0009-2880-8515","observed_orcids":["https://orcid.org/0009-0009-2880-8515","https://orcid.org/0000-0002-1305-4070"]},"institutions":[{"id":"https://openalex.org/I4210127958","display_name":"Universitas Dian Nuswantoro","ror":"https://ror.org/02csxcg02","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210127958"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Edi Noersasongko","raw_affiliation_strings":["Faculty of Computer Science , Universitas Dian Nuswantoro , Semarang , Indonesia , ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science , Universitas Dian Nuswantoro , Semarang , Indonesia , ,","institution_ids":["https://openalex.org/I4210127958"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032134691","display_name":"Ahmad Zainul Fanani","orcid":"https://orcid.org/0009-0008-1352-9401","observed_orcids":["https://orcid.org/0009-0008-1352-9401","https://orcid.org/0000-0002-8051-6458"]},"institutions":[{"id":"https://openalex.org/I4210127958","display_name":"Universitas Dian Nuswantoro","ror":"https://ror.org/02csxcg02","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210127958"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Ahmad Zainul Fanani","raw_affiliation_strings":["Faculty of Computer Science , Universitas Dian Nuswantoro , Semarang , Indonesia , ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science , Universitas Dian Nuswantoro , Semarang , Indonesia , ,","institution_ids":["https://openalex.org/I4210127958"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5116143267","display_name":"Deshinta Arrova Dewi","orcid":"https://orcid.org/0000-0003-1488-7696","observed_orcids":["https://orcid.org/0000-0003-1488-7696"]},"institutions":[{"id":"https://openalex.org/I12649496","display_name":"INTI International University","ror":"https://ror.org/03fj82m46","country_code":"MY","type":"education","lineage":["https://openalex.org/I12649496"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Deshinta Arrova Dewi","raw_affiliation_strings":["Faculty of Data Science and Information Technology , INTI International University , Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Data Science and Information Technology , INTI International University , Malaysia","institution_ids":["https://openalex.org/I12649496"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9940999746322632,"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":0.9940999746322632,"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":0.0019000000320374966,"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":0.001500000013038516,"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/named-entity-recognition","display_name":"named entity recognition","score":0.8069999814033508},{"id":"https://openalex.org/keywords/few-shot-learning","display_name":"few-shot learning","score":0.8700000047683716},{"id":"https://openalex.org/keywords/indonesian-language","display_name":"Indonesian language","score":0.7260000109672546},{"id":"https://openalex.org/keywords/low-resource-ner","display_name":"low-resource NER","score":0.8230000138282776},{"id":"https://openalex.org/keywords/skill-extraction","display_name":"skill extraction","score":0.6119999885559082},{"id":"https://openalex.org/keywords/open-innovation-ecosystems","display_name":"open innovation ecosystems","score":0.800000011920929},{"id":"https://openalex.org/keywords/competency-mapping","display_name":"competency mapping","score":0.5649999976158142}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8734999895095825},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.49410000443458557},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.4641000032424927},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.4625999927520752},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.44839999079704285},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4408000111579895},{"id":"https://openalex.org/C2777526511","wikidata":"https://www.wikidata.org/wiki/Q691543","display_name":"Pace","level":2,"score":0.436599999666214},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.39480000734329224},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.38609999418258667},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C2779207338","wikidata":"https://www.wikidata.org/wiki/Q9240","display_name":"Indonesian","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.32170000672340393},{"id":"https://openalex.org/C197914299","wikidata":"https://www.wikidata.org/wiki/Q18650","display_name":"Semantic memory","level":3,"score":0.3111000061035156},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.31060001254081726},{"id":"https://openalex.org/C69075417","wikidata":"https://www.wikidata.org/wiki/Q515701","display_name":"Linked data","level":3,"score":0.3091999888420105},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3084999918937683},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3028999865055084},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.29010000824928284},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.2833999991416931},{"id":"https://openalex.org/C85407183","wikidata":"https://www.wikidata.org/wiki/Q1045785","display_name":"Semantic network","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27950000762939453},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.2754000127315521},{"id":"https://openalex.org/C22607594","wikidata":"https://www.wikidata.org/wiki/Q5375150","display_name":"Enabling","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C2778139618","wikidata":"https://www.wikidata.org/wiki/Q13440398","display_name":"Workforce","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C2780535194","wikidata":"https://www.wikidata.org/wiki/Q309901","display_name":"Open data","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C6881194","wikidata":"https://www.wikidata.org/wiki/Q7449091","display_name":"Semantic technology","level":4,"score":0.25850000977516174},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.25589999556541443}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.14569/ijacsa.2026.0170141","doi":"https://doi.org/10.14569/ijacsa.2026.0170141","is_oa":true,"landing_page_url":"https://doi.org/10.14569/ijacsa.2026.0170141","pdf_url":"https://thesai.org/Downloads/Volume17No1/Paper_41-A_Few_Shot_Semantic_Meta_Learning_Framework.pdf","source":{"id":"https://openalex.org/S23629721","display_name":"International Journal of Advanced Computer Science and Applications","issn_l":"2156-5570","issn":["2156-5570","2158-107X"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","norway-1","poland-20","russia-white-list-3","vabb-shw"],"host_organization":"https://openalex.org/P4310311819","host_organization_name":"Science and Information Organization","host_organization_lineage":["https://openalex.org/P4310311819"],"host_organization_lineage_names":["Science and Information Organization"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Advanced Computer Science and Applications","raw_type":"journal-article"},{"id":"pmh:oai:thesai.org:666f0c6a-c8cb-41c3-8860-93c66f1fcc06","doi":null,"is_oa":true,"landing_page_url":"https://thesai.org/Publications/ViewPaper?Volume=17&Issue=1&Code=IJACSA&SerialNo=41","pdf_url":null,"source":{"id":"https://openalex.org/S23629721","display_name":"International Journal of Advanced Computer Science and Applications","issn_l":"2156-5570","issn":["2156-5570","2158-107X"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","norway-1","poland-20","russia-white-list-3","vabb-shw"],"host_organization":"https://openalex.org/P4310311819","host_organization_name":"Science and Information Organization","host_organization_lineage":["https://openalex.org/P4310311819"],"host_organization_lineage_names":["Science and Information Organization"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Journal of Advanced Computer Science and Applications, Vol. 17, No. 1 (2026), ISSN 2158-107X","raw_type":"text"}],"best_oa_location":{"id":"doi:10.14569/ijacsa.2026.0170141","doi":"https://doi.org/10.14569/ijacsa.2026.0170141","is_oa":true,"landing_page_url":"https://doi.org/10.14569/ijacsa.2026.0170141","pdf_url":"https://thesai.org/Downloads/Volume17No1/Paper_41-A_Few_Shot_Semantic_Meta_Learning_Framework.pdf","source":{"id":"https://openalex.org/S23629721","display_name":"International Journal of Advanced Computer Science and Applications","issn_l":"2156-5570","issn":["2156-5570","2158-107X"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","norway-1","poland-20","russia-white-list-3","vabb-shw"],"host_organization":"https://openalex.org/P4310311819","host_organization_name":"Science and Information Organization","host_organization_lineage":["https://openalex.org/P4310311819"],"host_organization_lineage_names":["Science and Information Organization"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Advanced Computer Science and Applications","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.7825999855995178},{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6773999929428101},{"id":"https://metadata.un.org/sdg/4","display_name":"Quality education","score":0.4156000018119812}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7127586857.pdf","grobid_xml":"https://content.openalex.org/works/W7127586857.grobid-xml"},"referenced_works_count":72,"referenced_works":["https://openalex.org/W3001428562","https://openalex.org/W3011594683","https://openalex.org/W3092172958","https://openalex.org/W3102295886","https://openalex.org/W3122230467","https://openalex.org/W3137156863","https://openalex.org/W3159597830","https://openalex.org/W3200005837","https://openalex.org/W4221025428","https://openalex.org/W4224235016","https://openalex.org/W4294956279","https://openalex.org/W4313213856","https://openalex.org/W4313471247","https://openalex.org/W4322742893","https://openalex.org/W4362635359","https://openalex.org/W4378470138","https://openalex.org/W4379231359","https://openalex.org/W4384697538","https://openalex.org/W4385368330","https://openalex.org/W4385567543","https://openalex.org/W4385572779","https://openalex.org/W4385647457","https://openalex.org/W4386424673","https://openalex.org/W4387068131","https://openalex.org/W4387848790","https://openalex.org/W4387998178","https://openalex.org/W4388840763","https://openalex.org/W4389967325","https://openalex.org/W4391817846","https://openalex.org/W4392023172","https://openalex.org/W4392430526","https://openalex.org/W4393272863","https://openalex.org/W4393323163","https://openalex.org/W4394709334","https://openalex.org/W4394743676","https://openalex.org/W4396613334","https://openalex.org/W4399116707","https://openalex.org/W4399533883","https://openalex.org/W4400350374","https://openalex.org/W4400604914","https://openalex.org/W4401023670","https://openalex.org/W4401118222","https://openalex.org/W4401237319","https://openalex.org/W4401454022","https://openalex.org/W4401486632","https://openalex.org/W4401836507","https://openalex.org/W4402134196","https://openalex.org/W4402352256","https://openalex.org/W4402923107","https://openalex.org/W4403304337","https://openalex.org/W4403493208","https://openalex.org/W4404035160","https://openalex.org/W4404799713","https://openalex.org/W4404886041","https://openalex.org/W4407880600","https://openalex.org/W4407964516","https://openalex.org/W4408157996","https://openalex.org/W4409060531","https://openalex.org/W4411332331","https://openalex.org/W4411729146","https://openalex.org/W4411976921","https://openalex.org/W4412018644","https://openalex.org/W4412107307","https://openalex.org/W4412449573","https://openalex.org/W4412468087","https://openalex.org/W4412756117","https://openalex.org/W4413061705","https://openalex.org/W4413683651","https://openalex.org/W4413841196","https://openalex.org/W4414086433","https://openalex.org/W4414300888","https://openalex.org/W4415350562"],"related_works":["https://openalex.org/W4391817846","https://openalex.org/W7172507527","https://openalex.org/W4414984557","https://openalex.org/W7129738895","https://openalex.org/W4403577311","https://openalex.org/W829114728","https://openalex.org/W4415590620","https://openalex.org/W6906577140","https://openalex.org/W4414606801","https://openalex.org/W4407025910"],"abstract_inverted_index":{"The":[0],"accelerating":[1],"pace":[2],"of":[3,13,126],"digital":[4],"transformation":[5],"is":[6,114],"reshaping":[7],"labour-market":[8],"dynamics,":[9],"driving":[10],"the":[11,18,71,108,111,197],"emergence":[12],"new":[14],"competencies,":[15],"and":[16,50,91,99,122,135,147,163,188,218],"intensifying":[17],"need":[19],"for":[20,38,79,102,178,206],"scalable":[21],"skill-intelligence":[22,208],"systems":[23],"within":[24],"open":[25,169],"innovation":[26,170,213],"ecosystems.":[27],"Yet,":[28],"research":[29],"on":[30,184],"Indonesian":[31,80],"Named":[32],"Entity":[33],"Recognition":[34],"(NER)":[35],"remains":[36],"limited":[37],"skill-extraction":[39],"tasks,":[40],"especially":[41],"in":[42,154],"low-resource":[43],"contexts":[44],"where":[45],"annotated":[46],"data":[47],"are":[48],"scarce":[49],"novel":[51],"skill":[52,81,105,165,194],"expressions":[53],"evolve":[54],"rapidly.":[55],"To":[56],"address":[57],"this":[58,60,172],"gap,":[59],"study":[61],"contributes":[62],"to":[63,95,192],"applied":[64],"Natural":[65],"Language":[66],"Processing":[67],"(NLP)":[68],"by":[69],"introducing":[70],"Few-Shot":[72],"Semantic":[73],"Meta-Learning":[74],"framework":[75,173],"with":[76],"CRF":[77,93,149],"(FSM-CRF)":[78],"entity":[82],"recognition,":[83],"which":[84],"integrates":[85],"semantic":[86,144,200],"span":[87,145],"representations,":[88],"episodic":[89,120],"meta-learning,":[90],"BIO-constrained":[92],"decoding":[94],"enhance":[96],"prototype":[97],"stability":[98],"entity-boundary":[100],"precision":[101],"complex,":[103],"multi-token":[104],"expressions.":[106],"Using":[107],"NERSkill.id":[109],"dataset,":[110],"proposed":[112],"model":[113],"evaluated":[115],"under":[116],"a":[117,124,175,203],"3-way,":[118],"10-shot":[119],"setting":[121],"achieves":[123],"micro-F1":[125],"73.84%,":[127],"outperforming":[128],"traditional":[129],"supervised":[130],"approaches":[131],"(IndoBERT":[132],"fine-tuning,":[133],"BiLSTM-CRF)":[134],"existing":[136],"few-shot":[137],"baselines.":[138],"Ablation":[139],"experiments":[140],"further":[141],"demonstrate":[142],"that":[143,210],"modelling":[146],"structured":[148],"inference":[150],"play":[151],"pivotal":[152],"roles":[153],"improving":[155],"robustness,":[156],"while":[157],"meta-learning":[158,201],"strengthens":[159],"adaptability":[160],"across":[161],"diverse":[162],"evolving":[164],"categories.":[166],"From":[167],"an":[168],"perspective,":[171],"offers":[174],"data-efficient":[176],"solution":[177],"dynamic":[179],"competency":[180],"mapping,":[181],"reducing":[182],"dependence":[183],"costly":[185],"annotation":[186],"pipelines":[187],"enabling":[189],"continuous":[190],"updates":[191],"workforce":[193,216],"taxonomies.":[195],"Overall,":[196],"findings":[198],"highlight":[199],"as":[202],"promising":[204],"foundation":[205],"next-generation":[207],"infrastructures":[209],"support":[211],"AI-enabled":[212],"management,":[214],"strategic":[215],"planning,":[217],"evidence-informed":[219],"policy":[220],"design.":[221]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-02-06T00:00:00"}