{"id":"https://openalex.org/W4200211261","doi":"https://doi.org/10.1007/s11192-021-04179-4","title":"PatentNet: multi-label classification of patent documents using deep learning based language understanding","display_name":"PatentNet: multi-label classification of patent documents using deep learning based language understanding","publication_year":2021,"publication_date":"2021-12-18","ids":{"openalex":"https://openalex.org/W4200211261","doi":"https://doi.org/10.1007/s11192-021-04179-4"},"language":"en","primary_location":{"id":"doi:10.1007/s11192-021-04179-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11192-021-04179-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11192-021-04179-4.pdf","source":{"id":"https://openalex.org/S148561398","display_name":"Scientometrics","issn_l":"0138-9130","issn":["0138-9130","1588-2861"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320108","host_organization_name":"Springer Nature (Netherlands)","host_organization_lineage":["https://openalex.org/P4310320108","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature (Netherlands)","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientometrics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11192-021-04179-4.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043280398","display_name":"Arousha Haghighian Roudsari","orcid":"https://orcid.org/0000-0001-6386-7806"},"institutions":[{"id":"https://openalex.org/I191879574","display_name":"Inha University","ror":"https://ror.org/01easw929","country_code":"KR","type":"education","lineage":["https://openalex.org/I191879574"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Arousha Haghighian Roudsari","raw_affiliation_strings":["Department of Industrial Engineering, Inha University, Incheon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Inha University, Incheon, South Korea","institution_ids":["https://openalex.org/I191879574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086745769","display_name":"Jafar Afshar","orcid":null},"institutions":[{"id":"https://openalex.org/I191879574","display_name":"Inha University","ror":"https://ror.org/01easw929","country_code":"KR","type":"education","lineage":["https://openalex.org/I191879574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jafar Afshar","raw_affiliation_strings":["Department of Industrial Engineering, Inha University, Incheon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Inha University, Incheon, South Korea","institution_ids":["https://openalex.org/I191879574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084025355","display_name":"Wookey Lee","orcid":"https://orcid.org/0000-0001-8586-4577"},"institutions":[{"id":"https://openalex.org/I191879574","display_name":"Inha University","ror":"https://ror.org/01easw929","country_code":"KR","type":"education","lineage":["https://openalex.org/I191879574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Wookey Lee","raw_affiliation_strings":["Department of Biomedical Science and Engineering, Inha University, Incheon, South Korea","Department of Industrial Engineering, Inha University, Incheon, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-8586-4577","affiliations":[{"raw_affiliation_string":"Department of Biomedical Science and Engineering, Inha University, Incheon, South Korea","institution_ids":["https://openalex.org/I191879574"]},{"raw_affiliation_string":"Department of Industrial Engineering, Inha University, Incheon, South Korea","institution_ids":["https://openalex.org/I191879574"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041799104","display_name":"Suan Lee","orcid":"https://orcid.org/0000-0002-3047-1167"},"institutions":[{"id":"https://openalex.org/I4210107562","display_name":"Semyung University","ror":"https://ror.org/01d100w34","country_code":"KR","type":"education","lineage":["https://openalex.org/I4210107562"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Suan Lee","raw_affiliation_strings":["School of Computer Science, Semyung University, Jecheon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Semyung University, Jecheon, South Korea","institution_ids":["https://openalex.org/I4210107562"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5043280398"],"corresponding_institution_ids":["https://openalex.org/I191879574"],"apc_list":{"value":2290,"currency":"EUR","value_usd":2890},"apc_paid":{"value":2290,"currency":"EUR","value_usd":2890},"fwci":6.2993,"has_fulltext":true,"cited_by_count":80,"citation_normalized_percentile":{"value":0.97067625,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"127","issue":"1","first_page":"207","last_page":"231"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9882000088691711,"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":0.9882000088691711,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9779999852180481,"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/T10856","display_name":"Intellectual Property and Patents","score":0.9765999913215637,"subfield":{"id":"https://openalex.org/subfields/1405","display_name":"Management of Technology and Innovation"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7914091944694519},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7399293780326843},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6794149279594421},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6243091821670532},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.5721726417541504},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5685783624649048},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5582213997840881},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5569312572479248},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5162286758422852},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47887223958969116},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44738179445266724},{"id":"https://openalex.org/keywords/document-classification","display_name":"Document classification","score":0.4280911982059479},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.33290255069732666},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07158589363098145}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7914091944694519},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7399293780326843},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6794149279594421},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6243091821670532},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.5721726417541504},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5685783624649048},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5582213997840881},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5569312572479248},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5162286758422852},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47887223958969116},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44738179445266724},{"id":"https://openalex.org/C2780479914","wikidata":"https://www.wikidata.org/wiki/Q302088","display_name":"Document classification","level":2,"score":0.4280911982059479},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33290255069732666},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07158589363098145},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s11192-021-04179-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11192-021-04179-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11192-021-04179-4.pdf","source":{"id":"https://openalex.org/S148561398","display_name":"Scientometrics","issn_l":"0138-9130","issn":["0138-9130","1588-2861"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320108","host_organization_name":"Springer Nature (Netherlands)","host_organization_lineage":["https://openalex.org/P4310320108","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature (Netherlands)","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientometrics","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:spr:scient:v:127:y:2022:i:1:d:10.1007_s11192-021-04179-4","is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s11192-021-04179-4","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s11192-021-04179-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11192-021-04179-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11192-021-04179-4.pdf","source":{"id":"https://openalex.org/S148561398","display_name":"Scientometrics","issn_l":"0138-9130","issn":["0138-9130","1588-2861"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320108","host_organization_name":"Springer Nature (Netherlands)","host_organization_lineage":["https://openalex.org/P4310320108","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature (Netherlands)","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientometrics","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4200211261.pdf","grobid_xml":"https://content.openalex.org/works/W4200211261.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W55768394","https://openalex.org/W95416943","https://openalex.org/W168564468","https://openalex.org/W1491576965","https://openalex.org/W1536515765","https://openalex.org/W1971579776","https://openalex.org/W2082036180","https://openalex.org/W2084319893","https://openalex.org/W2095705004","https://openalex.org/W2114367267","https://openalex.org/W2121879602","https://openalex.org/W2169863116","https://openalex.org/W2250539671","https://openalex.org/W2288737075","https://openalex.org/W2493916176","https://openalex.org/W2570926664","https://openalex.org/W2577564332","https://openalex.org/W2602917413","https://openalex.org/W2715319929","https://openalex.org/W2737136173","https://openalex.org/W2739996966","https://openalex.org/W2742947407","https://openalex.org/W2783785145","https://openalex.org/W2786979006","https://openalex.org/W2789330408","https://openalex.org/W2799302953","https://openalex.org/W2889961245","https://openalex.org/W2925605018","https://openalex.org/W2962784628","https://openalex.org/W2963250244","https://openalex.org/W2964110616","https://openalex.org/W2978746895","https://openalex.org/W2979826702","https://openalex.org/W3030266894","https://openalex.org/W3034156543","https://openalex.org/W3040400161","https://openalex.org/W3044968736","https://openalex.org/W3062383798","https://openalex.org/W3093466032","https://openalex.org/W3103587400","https://openalex.org/W3134304334","https://openalex.org/W3156333129","https://openalex.org/W4233344962","https://openalex.org/W4234620507","https://openalex.org/W4236765470","https://openalex.org/W6713213158","https://openalex.org/W6726030733","https://openalex.org/W7002306186"],"related_works":["https://openalex.org/W3031069236","https://openalex.org/W4313203076","https://openalex.org/W2521012290","https://openalex.org/W3049000890","https://openalex.org/W4389115964","https://openalex.org/W3096211175","https://openalex.org/W4385339003","https://openalex.org/W2129906471","https://openalex.org/W2775531141","https://openalex.org/W182138619"],"abstract_inverted_index":{"Abstract":[0],"Patent":[1],"classification":[2,34,56,60,178,204,219],"is":[3,43,57,82],"an":[4],"expensive":[5,78],"and":[6,26,79,96,103,137,180,214,233],"time-consuming":[7],"task":[8,35,61,81,142],"that":[9,190,209],"has":[10],"conventionally":[11],"been":[12],"performed":[13],"by":[14],"domain":[15,86],"experts.":[16],"However,":[17],"the":[18,21,27,30,33,70,125,129,140,152,167,170,192,197,201,212],"increase":[19],"in":[20,40,47,88,112],"number":[22,65],"of":[23,29,66,127,143,169],"filed":[24],"patents":[25],"complexity":[28],"documents":[31,42],"make":[32],"challenging.":[36],"The":[37,173],"text":[38,199],"used":[39,156,184],"patent":[41,55,90,98,145,158,177,198,203],"not":[44],"always":[45],"written":[46],"a":[48,58,63,216],"way":[49],"to":[50,165,223],"efficiently":[51],"convey":[52],"knowledge.":[53],"Moreover,":[54],"multi-label":[59,144,202],"with":[62,151,221],"large":[64],"labels,":[67],"which":[68],"makes":[69],"problem":[71],"even":[72],"more":[73],"complicated.":[74],"Hence,":[75],"automating":[76],"this":[77,119],"laborious":[80],"essential":[83,141],"for":[84,139,157,185],"assisting":[85],"experts":[87],"managing":[89],"documents,":[91],"facilitating":[92],"reliable":[93],"search,":[94],"retrieval,":[95],"further":[97],"analysis":[99],"tasks.":[100,117],"Transfer":[101],"learning":[102],"pre-trained":[104,130,193],"language":[105,131,194],"models":[106,150,195],"have":[107],"recently":[108],"achieved":[109],"state-of-the-art":[110,218],"results":[111],"many":[113],"Natural":[114],"Language":[115],"Processing":[116],"In":[118],"work,":[120],"we":[121],"focus":[122],"on":[123,196],"investigating":[124],"effect":[126],"fine-tuning":[128,191],"models,":[132],"namely,":[133],"BERT,":[134],"XLNet,":[135],"RoBERTa,":[136],"ELECTRA,":[138],"classification.":[146,159],"We":[147,160,188],"compare":[148],"these":[149],"baseline":[153,171],"deep-learning":[154],"approaches":[155],"use":[161],"various":[162],"word":[163],"embeddings":[164],"enhance":[166],"performance":[168,220],"models.":[172],"publicly":[174],"available":[175],"USPTO-2M":[176],"benchmark":[179],"M-patent":[181],"datasets":[182],"are":[183],"conducting":[186],"experiments.":[187],"conclude":[189],"improves":[200],"performance.":[205],"Our":[206],"findings":[207],"indicate":[208],"XLNet":[210],"performs":[211],"best":[213],"achieves":[215],"new":[217],"respect":[222],"precision,":[224],"recall,":[225],"F1":[226],"measure,":[227],"as":[228,230],"well":[229],"coverage":[231],"error,":[232],"LRAP.":[234]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":29},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":10}],"updated_date":"2026-04-25T08:17:42.794288","created_date":"2025-10-10T00:00:00"}
