{"id":"https://openalex.org/W4406535801","doi":"https://doi.org/10.1145/3712705","title":"Uncovering IT Career Path Patterns with Job Embedding-based Sequence Clustering","display_name":"Uncovering IT Career Path Patterns with Job Embedding-based Sequence Clustering","publication_year":2025,"publication_date":"2025-01-17","ids":{"openalex":"https://openalex.org/W4406535801","doi":"https://doi.org/10.1145/3712705"},"language":"en","primary_location":{"id":"doi:10.1145/3712705","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3712705","pdf_url":null,"source":{"id":"https://openalex.org/S4210170305","display_name":"ACM Transactions on Management Information Systems","issn_l":"2158-656X","issn":["2158-656X","2158-6578"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Management Information Systems","raw_type":"journal-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/A5101419246","display_name":"Hao Zhong","orcid":"https://orcid.org/0000-0001-5947-1729"},"institutions":[{"id":"https://openalex.org/I4210149577","display_name":"ESCP Business School","ror":"https://ror.org/040hhjv66","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210149577"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Hao Zhong","raw_affiliation_strings":["ESCP Business School, Paris, France"],"affiliations":[{"raw_affiliation_string":"ESCP Business School, Paris, France","institution_ids":["https://openalex.org/I4210149577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033864788","display_name":"Chuanren Liu","orcid":"https://orcid.org/0000-0001-9030-8495"},"institutions":[{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chuanren Liu","raw_affiliation_strings":["The University of Tennessee, Knoxville, United States"],"affiliations":[{"raw_affiliation_string":"The University of Tennessee, Knoxville, United States","institution_ids":["https://openalex.org/I75027704"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000306446","display_name":"Chaojiang Wu","orcid":"https://orcid.org/0000-0002-0047-9037"},"institutions":[{"id":"https://openalex.org/I149910238","display_name":"Kent State University","ror":"https://ror.org/049pfb863","country_code":"US","type":"education","lineage":["https://openalex.org/I149910238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chaojiang Wu","raw_affiliation_strings":["Kent State University, Kent, United States"],"affiliations":[{"raw_affiliation_string":"Kent State University, Kent, United States","institution_ids":["https://openalex.org/I149910238"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101419246"],"corresponding_institution_ids":["https://openalex.org/I4210149577"],"apc_list":null,"apc_paid":null,"fwci":1.5875,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83167888,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"16","issue":"2","first_page":"1","last_page":"32"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9814000129699707,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11122","display_name":"Online Learning and Analytics","score":0.9814000129699707,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9800999760627747,"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"}},{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9779000282287598,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"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/cluster-analysis","display_name":"Cluster analysis","score":0.6159818172454834},{"id":"https://openalex.org/keywords/career-path","display_name":"Career path","score":0.5427747964859009},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5365156531333923},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5001347064971924},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.393913596868515},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3388056755065918},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23060926795005798},{"id":"https://openalex.org/keywords/management","display_name":"Management","score":0.1814168393611908},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.09955653548240662},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.06076577305793762},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.058899909257888794}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6159818172454834},{"id":"https://openalex.org/C3019433489","wikidata":"https://www.wikidata.org/wiki/Q741939","display_name":"Career path","level":2,"score":0.5427747964859009},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5365156531333923},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5001347064971924},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.393913596868515},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3388056755065918},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23060926795005798},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.1814168393611908},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.09955653548240662},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.06076577305793762},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.058899909257888794},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3712705","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3712705","pdf_url":null,"source":{"id":"https://openalex.org/S4210170305","display_name":"ACM Transactions on Management Information Systems","issn_l":"2158-656X","issn":["2158-656X","2158-6578"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Management Information Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7884586587","display_name":null,"funder_award_id":"72371011","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W65563813","https://openalex.org/W1483072991","https://openalex.org/W1585151117","https://openalex.org/W1894414046","https://openalex.org/W1984920393","https://openalex.org/W1989018072","https://openalex.org/W1989318262","https://openalex.org/W1996881001","https://openalex.org/W1999161030","https://openalex.org/W2008312677","https://openalex.org/W2011428924","https://openalex.org/W2015523498","https://openalex.org/W2031804495","https://openalex.org/W2041181884","https://openalex.org/W2084311493","https://openalex.org/W2105211958","https://openalex.org/W2114177788","https://openalex.org/W2118775999","https://openalex.org/W2128728535","https://openalex.org/W2135964318","https://openalex.org/W2140178633","https://openalex.org/W2145244871","https://openalex.org/W2158217902","https://openalex.org/W2163922914","https://openalex.org/W2250539671","https://openalex.org/W2286878106","https://openalex.org/W2501271607","https://openalex.org/W2605192172","https://openalex.org/W2607515753","https://openalex.org/W2775023685","https://openalex.org/W2793648633","https://openalex.org/W2891796828","https://openalex.org/W2891893703","https://openalex.org/W2930957955","https://openalex.org/W2945464128","https://openalex.org/W2966274283","https://openalex.org/W3026770102","https://openalex.org/W3037383500","https://openalex.org/W3040864091","https://openalex.org/W3117329469","https://openalex.org/W3121353815","https://openalex.org/W3175930837","https://openalex.org/W3184843046","https://openalex.org/W3196024535","https://openalex.org/W4235169531","https://openalex.org/W4235539094","https://openalex.org/W4292928781","https://openalex.org/W4365799947","https://openalex.org/W6679651670","https://openalex.org/W7048653255"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W4298130764","https://openalex.org/W2804364458","https://openalex.org/W2931662336","https://openalex.org/W2077865380","https://openalex.org/W2132641928","https://openalex.org/W3006817050","https://openalex.org/W4310225030","https://openalex.org/W4243663106"],"abstract_inverted_index":{"Extracting":[0],"typical":[1],"career":[2,24,40,52,68,88,96,155,165],"paths":[3,97,156],"from":[4,150],"large-scale":[5],"and":[6,33,44,65,86,106,122,137,168],"unstructured":[7],"talent":[8],"profiles":[9,59],"has":[10],"recently":[11],"attracted":[12],"increasing":[13],"research":[14],"attention.":[15],"However,":[16],"various":[17],"challenges":[18],"arise":[19],"in":[20,30,76],"effectively":[21],"analyzing":[22,151],"self-reported":[23],"records.":[25],"Inspired":[26],"by":[27,71],"recent":[28],"advancements":[29],"neural":[31],"networks":[32],"embedding":[34],"models,":[35],"we":[36,56,80,125],"develop":[37],"a":[38],"novel":[39],"path":[41,53,69,89,166],"clustering":[42],"approach":[43,160],"apply":[45],"it":[46],"to":[47,132],"uncover":[48],"information":[49],"technology":[50],"(IT)":[51],"patterns.":[54],"Specifically,":[55],"construct":[57,87],"employment":[58],"of":[60,95],"over":[61,140],"60,000":[62],"IT":[63,164],"professionals,":[64],"form":[66],"their":[67,100],"sequences":[70],"chaining":[72],"the":[73,107,134,141],"job":[74,84,108,114],"records":[75],"each":[77,117],"profile.":[78],"Then":[79],"simultaneously":[81],"learn":[82],"cluster-wise":[83,93],"embeddings":[85,109],"clusters.":[90],"The":[91,147],"resultant":[92],"likelihoods":[94],"can":[98,110,161],"quantify":[99],"soft":[101],"bonding":[102],"with":[103,129],"different":[104],"clusters,":[105],"reveal":[111,169],"connections":[112],"among":[113],"titles":[115],"within":[116],"cluster.":[118],"With":[119],"both":[120],"real":[121,152],"simulated":[123],"data,":[124],"conduct":[126],"extensive":[127],"experiments":[128],"our":[130,159],"framework":[131],"establish":[133],"modeling":[135],"performance":[136],"great":[138],"improvement":[139],"traditional":[142],"optimal":[143],"matching":[144],"analysis":[145],"methods.":[146],"empirical":[148],"results":[149],"data":[153],"on":[154],"show":[157],"that":[158],"discover":[162],"distinct":[163],"patterns":[167],"valuable":[170],"insights.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}