{"id":"https://openalex.org/W3155371331","doi":"https://doi.org/10.1145/3442381.3449959","title":"Variable Interval Time Sequence Modeling for Career Trajectory Prediction: Deep Collaborative Perspective","display_name":"Variable Interval Time Sequence Modeling for Career Trajectory Prediction: Deep Collaborative Perspective","publication_year":2021,"publication_date":"2021-04-19","ids":{"openalex":"https://openalex.org/W3155371331","doi":"https://doi.org/10.1145/3442381.3449959","mag":"3155371331"},"language":"en","primary_location":{"id":"doi:10.1145/3442381.3449959","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3449959","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3442381.3449959","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100406893","display_name":"Chao Wang","orcid":"https://orcid.org/0000-0001-7717-447X"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Wang","raw_affiliation_strings":["University of Science and Technology of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049015446","display_name":"Hengshu Zhu","orcid":"https://orcid.org/0000-0003-4570-643X"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengshu Zhu","raw_affiliation_strings":["Baidu Inc., China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Inc., China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054404298","display_name":"Qiming Hao","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiming Hao","raw_affiliation_strings":["University of Science and Technology of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068405466","display_name":"Keli Xiao","orcid":"https://orcid.org/0000-0001-6494-1174"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Keli Xiao","raw_affiliation_strings":["Stony Brook University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stony Brook University, USA","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101862104","display_name":"Hui Xiong","orcid":"https://orcid.org/0000-0001-6016-6465"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hui Xiong","raw_affiliation_strings":["Rutgers University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.8578,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.96161662,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"612","last_page":"623"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9923999905586243,"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"}},"topics":[{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9923999905586243,"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/T13812","display_name":"AI and HR Technologies","score":0.9769999980926514,"subfield":{"id":"https://openalex.org/subfields/1407","display_name":"Organizational Behavior and Human Resource 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"}},{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9569000005722046,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7431095838546753},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7252594232559204},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.602070689201355},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5761831402778625},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5732501149177551},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5592315196990967},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.558817982673645},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.506062924861908},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.4858207702636719},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.46906113624572754},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46781277656555176},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.43991512060165405},{"id":"https://openalex.org/keywords/duration","display_name":"Duration (music)","score":0.4391057789325714},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.4335457980632782},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4299180507659912},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40919384360313416},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.31872615218162537},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09233242273330688},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08915674686431885}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7431095838546753},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7252594232559204},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.602070689201355},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5761831402778625},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5732501149177551},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5592315196990967},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.558817982673645},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.506062924861908},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.4858207702636719},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.46906113624572754},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46781277656555176},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.43991512060165405},{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.4391057789325714},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.4335457980632782},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4299180507659912},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40919384360313416},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.31872615218162537},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09233242273330688},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08915674686431885},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3442381.3449959","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3449959","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3442381.3449959","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3449959","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W48288425","https://openalex.org/W1985854669","https://openalex.org/W1990588199","https://openalex.org/W2011669536","https://openalex.org/W2042281163","https://openalex.org/W2054141820","https://openalex.org/W2082404215","https://openalex.org/W2093473165","https://openalex.org/W2105621451","https://openalex.org/W2128084896","https://openalex.org/W2143612262","https://openalex.org/W2147880316","https://openalex.org/W2157881433","https://openalex.org/W2171279286","https://openalex.org/W2187089797","https://openalex.org/W2246827810","https://openalex.org/W2317859022","https://openalex.org/W2474973331","https://openalex.org/W2482567233","https://openalex.org/W2507440079","https://openalex.org/W2565962065","https://openalex.org/W2605350416","https://openalex.org/W2613228905","https://openalex.org/W2625746539","https://openalex.org/W2626479615","https://openalex.org/W2725606191","https://openalex.org/W2740920897","https://openalex.org/W2751933316","https://openalex.org/W2809112621","https://openalex.org/W2894982503","https://openalex.org/W2897356390","https://openalex.org/W2902847392","https://openalex.org/W2904064004","https://openalex.org/W2904937533","https://openalex.org/W2912404939","https://openalex.org/W2952179887","https://openalex.org/W2952718163","https://openalex.org/W2962817261","https://openalex.org/W2963218586","https://openalex.org/W2970585579","https://openalex.org/W2987222756","https://openalex.org/W2996931760","https://openalex.org/W2997353686","https://openalex.org/W2998892931","https://openalex.org/W3080903012","https://openalex.org/W3098231197","https://openalex.org/W4250661537","https://openalex.org/W6668990524"],"related_works":["https://openalex.org/W2772628444","https://openalex.org/W2735929803","https://openalex.org/W4220714703","https://openalex.org/W1484355083","https://openalex.org/W3008845055","https://openalex.org/W2098758514","https://openalex.org/W4376854386","https://openalex.org/W2202724490","https://openalex.org/W2508671622","https://openalex.org/W2556532874"],"abstract_inverted_index":{"In":[0],"today\u2019s":[1],"fast-evolving":[2],"job":[3],"market,":[4],"the":[5,11,25,30,50,54,60,65,69,83,123,130,169,208,230,234],"timely":[6],"and":[7,23,63,150,172,233],"effective":[8],"understanding":[9,129],"of":[10,14,82,120,133,164,168,202],"career":[12,27,43,111,131,148,248],"trajectories":[13,132],"talents":[15],"can":[16],"help":[17],"them":[18],"quickly":[19],"develop":[20,77],"necessary":[21],"skills":[22],"make":[24],"right":[26,31,55,61,66],"transitions":[28],"at":[29],"time.":[32],"However,":[33],"it":[34],"is":[35,87,118,200],"a":[36,41,108,141,188],"non-trivial":[37],"task":[38],"for":[39,52,57,68,79,127,147,174,181,210,247],"developing":[40],"successful":[42],"trajectory":[44,112,249],"prediction":[45,113],"method,":[46],"which":[47,117,158],"should":[48],"have":[49,73,218],"abilities":[51,98,126],"finding":[53],"timing":[56],"job-hopping,":[58],"identifying":[59],"companies,":[62,171],"matching":[64],"positions":[67,173],"candidates.":[70],"While":[71],"people":[72],"been":[74],"trying":[75],"to":[76,94,192,226],"solutions":[78],"providing":[80,122],"some":[81],"above":[84,124],"abilities,":[85],"there":[86],"no":[88],"total":[89],"solution":[90],"or":[91],"complete":[92],"framework":[93],"integrate":[95],"all":[96,244],"these":[97],"together.":[99],"To":[100],"this":[101,104,136],"end,":[102],"in":[103],"paper,":[105],"we":[106,138,177,186,217],"propose":[107,187],"unified":[109],"time-aware":[110,204],"framework,":[114],"namely":[115],"TACTP,":[116],"capable":[119,201],"jointly":[121],"three":[125],"better":[128],"talents.":[134],"Along":[135],"line,":[137],"first":[139],"exploit":[140],"hierarchical":[142],"deep":[143],"sequential":[144],"modeling":[145],"network":[146],"embedding":[149],"extract":[151],"latent":[152],"talent":[153],"factors":[154],"from":[155],"multiple":[156],"networks,":[157],"are":[159],"designed":[160],"with":[161],"different":[162],"functions":[163],"handling":[165],"related":[166],"issues":[167],"timing,":[170],"job-hopping.":[175],"Then,":[176],"perform":[178],"collaborative":[179],"filtering":[180],"generating":[182,203],"personalized":[183],"predictions.":[184],"Furthermore,":[185],"temporal":[189,195],"encoding":[190],"mechanism":[191],"handle":[193],"dynamic":[194],"information":[196],"so":[197],"that":[198,237],"TACTP":[199,228,238],"predictions":[205],"by":[206],"addressing":[207],"challenges":[209],"variable":[211],"interval":[212],"time":[213],"sequence":[214],"modeling.":[215],"Finally,":[216],"conducted":[219],"extensive":[220],"experiments":[221],"on":[222,243],"large-scale":[223],"real-world":[224],"data":[225],"evaluate":[227],"against":[229],"state-of-the-art":[231],"baselines,":[232],"results":[235],"show":[236],"has":[239],"advantages":[240],"over":[241],"baselines":[242],"targeted":[245],"tasks":[246],"prediction.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}