{"id":"https://openalex.org/W4318813940","doi":"https://doi.org/10.1145/3528588.3528658","title":"Supporting systematic literature reviews using deep-learning-based language models","display_name":"Supporting systematic literature reviews using deep-learning-based language models","publication_year":2022,"publication_date":"2022-05-21","ids":{"openalex":"https://openalex.org/W4318813940","doi":"https://doi.org/10.1145/3528588.3528658"},"language":"en","primary_location":{"id":"doi:10.1145/3528588.3528658","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3528588.3528658","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3528588.3528658","source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st International Workshop on Natural Language-based Software Engineering","raw_type":"proceedings-article"},"type":"review","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3528588.3528658","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018745656","display_name":"Rand Alchokr","orcid":"https://orcid.org/0000-0003-0112-5430"},"institutions":[{"id":"https://openalex.org/I95793202","display_name":"Otto-von-Guericke-Universit\u00e4t Magdeburg","ror":"https://ror.org/00ggpsq73","country_code":"DE","type":"education","lineage":["https://openalex.org/I95793202"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Rand Alchokr","raw_affiliation_strings":["Otto-von-Guericke University, Magdeburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Otto-von-Guericke University, Magdeburg, Germany","institution_ids":["https://openalex.org/I95793202"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007433852","display_name":"Manoj R. Borkar","orcid":"https://orcid.org/0000-0003-0582-1978"},"institutions":[{"id":"https://openalex.org/I95793202","display_name":"Otto-von-Guericke-Universit\u00e4t Magdeburg","ror":"https://ror.org/00ggpsq73","country_code":"DE","type":"education","lineage":["https://openalex.org/I95793202"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Manoj Borkar","raw_affiliation_strings":["Otto-von-Guericke University, Magdeburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Otto-von-Guericke University, Magdeburg, Germany","institution_ids":["https://openalex.org/I95793202"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025042882","display_name":"Sharanya Thotadarya","orcid":null},"institutions":[{"id":"https://openalex.org/I95793202","display_name":"Otto-von-Guericke-Universit\u00e4t Magdeburg","ror":"https://ror.org/00ggpsq73","country_code":"DE","type":"education","lineage":["https://openalex.org/I95793202"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sharanya Thotadarya","raw_affiliation_strings":["Otto-von-Guericke University, Magdeburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Otto-von-Guericke University, Magdeburg, Germany","institution_ids":["https://openalex.org/I95793202"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042946019","display_name":"Gunter Saake","orcid":"https://orcid.org/0000-0001-9576-8474"},"institutions":[{"id":"https://openalex.org/I95793202","display_name":"Otto-von-Guericke-Universit\u00e4t Magdeburg","ror":"https://ror.org/00ggpsq73","country_code":"DE","type":"education","lineage":["https://openalex.org/I95793202"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gunter Saake","raw_affiliation_strings":["Otto-von-Guericke University, Magdeburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Otto-von-Guericke University, Magdeburg, Germany","institution_ids":["https://openalex.org/I95793202"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086853013","display_name":"Thomas Leich","orcid":"https://orcid.org/0000-0001-9580-7728"},"institutions":[{"id":"https://openalex.org/I4210138551","display_name":"University Hospital Magdeburg","ror":"https://ror.org/03m04df46","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I4210138551"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Leich","raw_affiliation_strings":["Harz University, Magdeburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harz University, Magdeburg, Germany","institution_ids":["https://openalex.org/I4210138551"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3046,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.67279412,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"67","last_page":"74"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9919999837875366,"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":0.9919999837875366,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.986299991607666,"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.9799000024795532,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8414496779441833},{"id":"https://openalex.org/keywords/paragraph","display_name":"Paragraph","score":0.7508467435836792},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7397135496139526},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.657319962978363},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5572108030319214},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.537548303604126},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5244957804679871},{"id":"https://openalex.org/keywords/systematic-review","display_name":"Systematic review","score":0.5222338438034058},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5063663721084595},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.47933468222618103},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.47294116020202637},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4493709206581116},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39144593477249146},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.32498055696487427},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.09961071610450745}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8414496779441833},{"id":"https://openalex.org/C2777206241","wikidata":"https://www.wikidata.org/wiki/Q194431","display_name":"Paragraph","level":2,"score":0.7508467435836792},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7397135496139526},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.657319962978363},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5572108030319214},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.537548303604126},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5244957804679871},{"id":"https://openalex.org/C189708586","wikidata":"https://www.wikidata.org/wiki/Q1504425","display_name":"Systematic review","level":3,"score":0.5222338438034058},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5063663721084595},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.47933468222618103},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.47294116020202637},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4493709206581116},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39144593477249146},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32498055696487427},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.09961071610450745},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3528588.3528658","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3528588.3528658","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3528588.3528658","source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st International Workshop on Natural Language-based Software Engineering","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3528588.3528658","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3528588.3528658","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3528588.3528658","source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st International Workshop on Natural Language-based Software Engineering","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4318813940.pdf","grobid_xml":"https://content.openalex.org/works/W4318813940.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1573470912","https://openalex.org/W1973251307","https://openalex.org/W2043634247","https://openalex.org/W2071055029","https://openalex.org/W2084722535","https://openalex.org/W2097198341","https://openalex.org/W2144326572","https://openalex.org/W2152790380","https://openalex.org/W2196942307","https://openalex.org/W2612764117","https://openalex.org/W2787560479","https://openalex.org/W2963026768","https://openalex.org/W2970641574","https://openalex.org/W2985804587","https://openalex.org/W3022955783","https://openalex.org/W4302617179"],"related_works":["https://openalex.org/W4288365749","https://openalex.org/W2936497627","https://openalex.org/W3013624417","https://openalex.org/W4287826556","https://openalex.org/W3098382480","https://openalex.org/W4287598411","https://openalex.org/W3100913109","https://openalex.org/W3198458223","https://openalex.org/W3126642501","https://openalex.org/W2964413124"],"abstract_inverted_index":{"Background:":[0],"Systematic":[1,27,76],"Literature":[2,28,77],"Reviews":[3,78],"are":[4],"an":[5,91],"important":[6],"research":[7,19],"method":[8],"for":[9,79,196],"gathering":[10],"and":[11,34,66,117,180,207,236],"evaluating":[12],"the":[13,22,72,82,100,151,160,177,181,185,198,205,230],"available":[14],"evidence":[15],"regarding":[16],"a":[17,26,55,67,129,218],"specific":[18],"topic.":[20],"However,":[21],"process":[23,44],"of":[24,47,75,85,102,158,170,176,184,200],"conducting":[25],"Review":[29],"manually":[30,95],"can":[31,203],"be":[32],"difficult":[33],"time-consuming.":[35],"For":[36],"this":[37,43],"reason,":[38],"researchers":[39,228],"aim":[40],"to":[41,70,98,119,132,221,226],"semi-automate":[42],"or":[45],"some":[46],"its":[48],"phases.":[49],"Aim:":[50],"We":[51,89],"aimed":[52],"at":[53,146],"using":[54,93,148,192],"deep-learning":[56,194],"based":[57,143],"contextualized":[58,121],"embeddings":[59,122],"clustering":[60,105,142],"technique":[61,219],"involving":[62],"transformer-based":[63,111],"language":[64,113],"models":[65,108,114],"weighted":[68,130],"scheme":[69,131],"accelerate":[71,204],"conduction":[73],"phase":[74],"efficiently":[80],"scanning":[81,206],"initial":[83],"set":[84],"retrieved":[86],"publications.":[87,135],"Method:":[88],"performed":[90],"experiment":[92],"two":[94,103],"conducted":[96],"SLRs":[97],"evaluate":[99],"performance":[101],"deep-learning-based":[104],"models.":[106],"These":[107],"build":[109],"on":[110,123,144],"deep":[112],"(i.e.,":[115],"BERT":[116],"S-BERT)":[118],"extract":[120],"different":[124],"text":[125],"levels":[126],"along":[127],"with":[128],"cluster":[133,179],"similar":[134],"Results:":[136],"Our":[137],"primary":[138,167,201],"results":[139,212],"show":[140],"that":[141,191],"embedding":[145],"paragraph-level":[147],"S-BERT-paragraph":[149],"represents":[150],"best":[152],"performing":[153],"model":[154],"setting":[155],"in":[156],"terms":[157],"optimizing":[159],"required":[161],"parameters":[162],"such":[163,217],"as":[164,174],"correctly":[165],"identifying":[166],"studies,":[168],"number":[169],"additional":[171],"documents":[172],"identified":[173],"part":[175],"relevant":[178,232],"execution":[182],"time":[183],"experiments.":[186],"Conclusions:":[187],"The":[188],"findings":[189],"indicate":[190],"natural-language-based":[193],"architectures":[195],"semi-automating":[197],"selection":[199],"studies":[202],"identification":[208],"process.":[209],"While":[210],"our":[211],"represent":[213],"first":[214],"insights":[215],"only,":[216],"seems":[220],"enhance":[222],"SLR":[223],"process,":[224],"promising":[225],"help":[227],"identify":[229],"most":[231],"publications":[233],"more":[234],"quickly":[235],"efficiently.":[237]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
