{"id":"https://openalex.org/W4318147160","doi":"https://doi.org/10.1109/bigdata55660.2022.10020405","title":"Learning skills adjacency representations for optimized reskilling recommendations","display_name":"Learning skills adjacency representations for optimized reskilling recommendations","publication_year":2022,"publication_date":"2022-12-17","ids":{"openalex":"https://openalex.org/W4318147160","doi":"https://doi.org/10.1109/bigdata55660.2022.10020405"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata55660.2022.10020405","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020405","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008879114","display_name":"Saksham Gandhi","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Saksham Gandhi","raw_affiliation_strings":["IBM,New York,USA","IBM, New York, USA"],"affiliations":[{"raw_affiliation_string":"IBM,New York,USA","institution_ids":["https://openalex.org/I1341412227"]},{"raw_affiliation_string":"IBM, New York, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032972359","display_name":"Raj Nagesh","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raj Nagesh","raw_affiliation_strings":["IBM,USA","IBM, USA"],"affiliations":[{"raw_affiliation_string":"IBM,USA","institution_ids":["https://openalex.org/I1341412227"]},{"raw_affiliation_string":"IBM, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011183160","display_name":"Subhro Das","orcid":"https://orcid.org/0000-0002-7610-2738"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Subhro Das","raw_affiliation_strings":["IBM Research,MIT-IBM Watson AI Lab,Cambridge,USA","MIT-IBM Watson AI Lab, IBM Research, Cambridge, USA"],"affiliations":[{"raw_affiliation_string":"IBM Research,MIT-IBM Watson AI Lab,Cambridge,USA","institution_ids":["https://openalex.org/I1341412227"]},{"raw_affiliation_string":"MIT-IBM Watson AI Lab, IBM Research, Cambridge, USA","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008879114"],"corresponding_institution_ids":["https://openalex.org/I1341412227"],"apc_list":null,"apc_paid":null,"fwci":0.2909,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.64666667,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"2253","last_page":"2258"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12501","display_name":"Digital Economy and Work Transformation","score":0.9783999919891357,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12501","display_name":"Digital Economy and Work Transformation","score":0.9783999919891357,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12028","display_name":"Knowledge Management and Sharing","score":0.9690999984741211,"subfield":{"id":"https://openalex.org/subfields/3315","display_name":"Communication"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10003","display_name":"Innovation and Knowledge Management","score":0.9638000130653381,"subfield":{"id":"https://openalex.org/subfields/1408","display_name":"Strategy and Management"},"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":0.747718870639801},{"id":"https://openalex.org/keywords/word2vec","display_name":"Word2vec","score":0.6823865175247192},{"id":"https://openalex.org/keywords/workforce","display_name":"Workforce","score":0.5718282461166382},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5254434943199158},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4462531507015228},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4366842210292816},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.4208069145679474},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3912903070449829},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3814609944820404}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.747718870639801},{"id":"https://openalex.org/C2776461190","wikidata":"https://www.wikidata.org/wiki/Q22673982","display_name":"Word2vec","level":3,"score":0.6823865175247192},{"id":"https://openalex.org/C2778139618","wikidata":"https://www.wikidata.org/wiki/Q13440398","display_name":"Workforce","level":2,"score":0.5718282461166382},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5254434943199158},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4462531507015228},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4366842210292816},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.4208069145679474},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3912903070449829},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3814609944820404},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata55660.2022.10020405","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020405","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.6800000071525574,"id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1614298861","https://openalex.org/W1682403713","https://openalex.org/W2033912020","https://openalex.org/W2228966521","https://openalex.org/W2586844573","https://openalex.org/W2613228905","https://openalex.org/W2804936679","https://openalex.org/W2809300179","https://openalex.org/W2896457183","https://openalex.org/W2901765663","https://openalex.org/W2904185051","https://openalex.org/W2912141395","https://openalex.org/W2964424700","https://openalex.org/W2978017171","https://openalex.org/W2987222756","https://openalex.org/W2991532994","https://openalex.org/W3000184126","https://openalex.org/W3004244221","https://openalex.org/W3006280721","https://openalex.org/W3020026958","https://openalex.org/W3023363467","https://openalex.org/W3034199299","https://openalex.org/W3097821835","https://openalex.org/W3100434407","https://openalex.org/W3117329469","https://openalex.org/W3125498346","https://openalex.org/W3137586694","https://openalex.org/W3174822636","https://openalex.org/W3184230151","https://openalex.org/W4281251945","https://openalex.org/W4287867774","https://openalex.org/W4288398504","https://openalex.org/W6766003122"],"related_works":["https://openalex.org/W2980729574","https://openalex.org/W1560851690","https://openalex.org/W3092047717","https://openalex.org/W2905749112","https://openalex.org/W2346530426","https://openalex.org/W3099354896","https://openalex.org/W2890749918","https://openalex.org/W4287599800","https://openalex.org/W2772765860","https://openalex.org/W4312264180"],"abstract_inverted_index":{"Today\u2019s":[0],"fast":[1],"changing":[2],"workplace":[3],"necessitates":[4],"constant":[5],"reskilling":[6,20,54,123],"of":[7,59,66],"the":[8,12,127,135],"workforce":[9],"at":[10],"both":[11,139],"corporate":[13],"and":[14,29,70,86,120,141],"national":[15],"level.":[16],"Current":[17],"approaches":[18],"to":[19,32,52,80,92,106,110,121,137,144,150],"depend":[21],"on":[22,35,63,116,126],"manual":[23,36],"logic,":[24],"which":[25,108],"can":[26],"be":[27],"time-consuming":[28],"expensive":[30],"due":[31],"their":[33,113,117,147],"dependence":[34],"labour.":[37],"In":[38],"this":[39,74,102],"paper,":[40],"we":[41],"propose":[42],"a":[43,50,64],"scalable":[44],"machine-learning":[45],"driven":[46],"alternative":[47],"by":[48,75],"introducing":[49],"method":[51],"make":[53,93],"recommendations":[55],"using":[56,84],"word":[57],"embeddings":[58,79],"skill":[60,82,129],"keywords":[61,83],"trained":[62],"corpus":[65],"historical":[67],"job":[68],"listings":[69],"resumes.":[71],"We":[72],"achieve":[73],"training":[76],"dense":[77],"vector":[78],"represent":[81],"Word2Vec":[85],"fine-tuned":[87],"BERT":[88],"models,":[89],"allowing":[90],"us":[91],"comparisons":[94],"between":[95],"skills.":[96],"Given":[97],"an":[98],"individual\u2019s":[99],"current":[100],"skills,":[101],"model":[103],"is":[104],"leveraged":[105],"identify":[107],"skills":[109],"prioritize":[111],"for":[112],"development":[114],"based":[115,125],"target":[118],"role":[119],"recommend":[122],"plans":[124],"identified":[128],"gap.":[130],"The":[131],"proposed":[132],"framework":[133],"has":[134],"potential":[136],"aid":[138],"public":[140],"private":[142],"organizations":[143],"better":[145],"direct":[146],"educational":[148],"resources":[149],"individuals.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}