{"id":"https://openalex.org/W4401907824","doi":"https://doi.org/10.3390/make6030096","title":"Assessing Fine-Tuned NER Models with Limited Data in French: Automating Detection of New Technologies, Technological Domains, and Startup Names in Renewable Energy","display_name":"Assessing Fine-Tuned NER Models with Limited Data in French: Automating Detection of New Technologies, Technological Domains, and Startup Names in Renewable Energy","publication_year":2024,"publication_date":"2024-08-27","ids":{"openalex":"https://openalex.org/W4401907824","doi":"https://doi.org/10.3390/make6030096"},"language":"en","primary_location":{"id":"doi:10.3390/make6030096","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make6030096","pdf_url":"https://www.mdpi.com/2504-4990/6/3/96/pdf?version=1724759848","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-4990/6/3/96/pdf?version=1724759848","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113350659","display_name":"Connor MacLean","orcid":"https://orcid.org/0009-0007-5042-4337"},"institutions":[{"id":"https://openalex.org/I2801509770","display_name":"Institut National des Sciences Appliqu\u00e9es de Strasbourg","ror":"https://ror.org/001nta019","country_code":"FR","type":"education","lineage":["https://openalex.org/I2801509770"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Connor MacLean","raw_affiliation_strings":["INSA Strasbourg, 67000 Strasbourg, France"],"raw_orcid":"https://orcid.org/0009-0007-5042-4337","affiliations":[{"raw_affiliation_string":"INSA Strasbourg, 67000 Strasbourg, France","institution_ids":["https://openalex.org/I2801509770"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026220468","display_name":"Denis Cavallucci","orcid":"https://orcid.org/0000-0003-1815-5601"},"institutions":[{"id":"https://openalex.org/I2801509770","display_name":"Institut National des Sciences Appliqu\u00e9es de Strasbourg","ror":"https://ror.org/001nta019","country_code":"FR","type":"education","lineage":["https://openalex.org/I2801509770"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Denis Cavallucci","raw_affiliation_strings":["INSA Strasbourg, 67000 Strasbourg, France"],"raw_orcid":"https://orcid.org/0000-0003-1815-5601","affiliations":[{"raw_affiliation_string":"INSA Strasbourg, 67000 Strasbourg, France","institution_ids":["https://openalex.org/I2801509770"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5026220468","https://openalex.org/A5113350659"],"corresponding_institution_ids":["https://openalex.org/I2801509770"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.2233,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.47183349,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"6","issue":"3","first_page":"1953","last_page":"1968"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9851999878883362,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9851999878883362,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9828000068664551,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9824000000953674,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.6912568211555481},{"id":"https://openalex.org/keywords/renewable-energy","display_name":"Renewable energy","score":0.5705603361129761},{"id":"https://openalex.org/keywords/energy-sector","display_name":"Energy sector","score":0.5626003742218018},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5292959213256836},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5246684551239014},{"id":"https://openalex.org/keywords/neutrality","display_name":"Neutrality","score":0.4873224198818207},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4678930342197418},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.4416831135749817},{"id":"https://openalex.org/keywords/emerging-technologies","display_name":"Emerging technologies","score":0.4309975504875183},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3410486578941345},{"id":"https://openalex.org/keywords/environmental-economics","display_name":"Environmental economics","score":0.12303954362869263},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12071254849433899}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6912568211555481},{"id":"https://openalex.org/C188573790","wikidata":"https://www.wikidata.org/wiki/Q12705","display_name":"Renewable energy","level":2,"score":0.5705603361129761},{"id":"https://openalex.org/C2985347565","wikidata":"https://www.wikidata.org/wiki/Q2151621","display_name":"Energy sector","level":2,"score":0.5626003742218018},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5292959213256836},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5246684551239014},{"id":"https://openalex.org/C2779581858","wikidata":"https://www.wikidata.org/wiki/Q9049677","display_name":"Neutrality","level":2,"score":0.4873224198818207},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4678930342197418},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.4416831135749817},{"id":"https://openalex.org/C207267971","wikidata":"https://www.wikidata.org/wiki/Q120208","display_name":"Emerging technologies","level":2,"score":0.4309975504875183},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3410486578941345},{"id":"https://openalex.org/C134560507","wikidata":"https://www.wikidata.org/wiki/Q753291","display_name":"Environmental economics","level":1,"score":0.12303954362869263},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12071254849433899},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/make6030096","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make6030096","pdf_url":"https://www.mdpi.com/2504-4990/6/3/96/pdf?version=1724759848","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:HAL:hal-04692439v1","is_oa":true,"landing_page_url":"https://hal.science/hal-04692439","pdf_url":"https://hal.science/hal-04692439/document","source":{"id":"https://openalex.org/S4406922466","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction, 2024, 6 (3), pp.1953-1968. ⟨10.3390/make6030096⟩","raw_type":"Journal articles"},{"id":"pmh:oai:doaj.org/article:de1b70a9b3eb429497bf1540b55be0bf","is_oa":true,"landing_page_url":"https://doaj.org/article/de1b70a9b3eb429497bf1540b55be0bf","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction, Vol 6, Iss 3, Pp 1953-1968 (2024)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2504-4990/6/3/96/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/make6030096","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"Text"},{"id":"pmh:oai:univoak.eu:islandora_171737","is_oa":true,"landing_page_url":"https://univoak.eu/islandora/object/islandora%3A171737","pdf_url":null,"source":{"id":"https://openalex.org/S4306402449","display_name":"univOAK (4 institutions : Universit\u00e9 de Strasbourg, Universit\u00e9 de Haute Alsace, INSA Strasbourg, Biblioth\u00e8que Nationale et Universitaire de Strasbourg)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210100283","host_organization_name":"Laboratoire des Sciences de l'Ing\u00e9nieur, de l'Informatique et de l'Imagerie","host_organization_lineage":["https://openalex.org/I4210100283"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.3390/make6030096","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make6030096","pdf_url":"https://www.mdpi.com/2504-4990/6/3/96/pdf?version=1724759848","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310654","display_name":"Indian National Science Academy","ror":"https://ror.org/051475v86"},{"id":"https://openalex.org/F4320323744","display_name":"\u00c9lectricit\u00e9 de France","ror":"https://ror.org/03wb8xz10"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4401907824.pdf","grobid_xml":"https://content.openalex.org/works/W4401907824.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W2065285441","https://openalex.org/W2120844411","https://openalex.org/W2725541287","https://openalex.org/W2962949934","https://openalex.org/W2979826702","https://openalex.org/W2986154550","https://openalex.org/W3103187652","https://openalex.org/W3213422511","https://openalex.org/W4376867987","https://openalex.org/W4392271257","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W2472237388","https://openalex.org/W4211168656","https://openalex.org/W2572059069","https://openalex.org/W2547660074","https://openalex.org/W4241049928","https://openalex.org/W2492807369","https://openalex.org/W2575291552","https://openalex.org/W1991323803","https://openalex.org/W2493806475","https://openalex.org/W2072053626"],"abstract_inverted_index":{"Achieving":[0],"carbon":[1],"neutrality":[2],"by":[3],"2050":[4],"requires":[5],"unprecedented":[6],"technological,":[7],"economic,":[8],"and":[9,27,46,61,80,104,194],"sociological":[10],"changes.":[11],"With":[12],"time":[13],"as":[14,85,188,190],"a":[15,68,126],"scarce":[16],"resource,":[17],"it":[18],"is":[19,74,88,180],"crucial":[20],"to":[21,29,35,44,76,93,121,145,153,160,168,182,191,207,216],"base":[22],"decisions":[23],"on":[24,67,90,142],"relevant":[25,41],"facts":[26],"information":[28,42],"avoid":[30],"misdirection.":[31],"This":[32,72,149,178,212],"study":[33],"aims":[34],"help":[36],"decision":[37],"makers":[38],"quickly":[39],"find":[40],"related":[43,92],"companies":[45,226],"organizations":[47],"in":[48,99,107,202,205,233],"the":[49,86,100,108,114,117,134,137,155,170,203,225,234],"renewable":[50],"energy":[51,222],"sector.":[52],"In":[53,83],"this":[54],"study,":[55],"we":[56,95],"propose":[57],"fine-tuning":[58],"five":[59],"RNN":[60],"transformer":[62],"models":[63,159],"trained":[64,141],"for":[65],"French":[66],"new":[69,81,185,231],"category,":[70],"\u201cTECH\u201d.":[71],"category":[73],"used":[75,181],"classify":[77],"technological":[78],"domains":[79,196,223],"products.":[82],"addition,":[84],"model":[87,120,138],"fine-tuned":[89],"news":[91,204],"startups,":[94],"note":[96],"an":[97],"improvement":[98],"detection":[101],"of":[102,116,129,136,157,173,220],"startup":[103],"company":[105,186],"names":[106],"\u201cORG\u201d":[109],"category.":[110],"We":[111,132],"further":[112,214],"explore":[113],"capacities":[115],"most":[118],"effective":[119],"accurately":[122],"predict":[123],"entities":[124],"using":[125],"small":[127],"amount":[128],"training":[130,176],"data.":[131,177],"show":[133],"progression":[135],"from":[139],"being":[140,200],"several":[143,146],"hundred":[144],"thousand":[147],"annotations.":[148],"analysis":[150],"allows":[151,215],"us":[152,167],"demonstrate":[154],"potential":[156],"these":[158],"extract":[161,184,192],"insights":[162],"without":[163],"large":[164],"corpora,":[165],"allowing":[166],"reduce":[169],"long":[171],"process":[172],"annotating":[174],"custom":[175],"approach":[179,213],"automatically":[183],"mentions":[187,219],"well":[189],"technologies":[193,232],"technology":[195],"that":[197,227],"are":[198,228],"currently":[199],"discussed":[201],"order":[206],"better":[208],"analyze":[209],"industry":[210],"trends.":[211],"group":[217],"together":[218],"specific":[221],"with":[224],"actively":[229],"developing":[230],"field.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}