{"id":"https://openalex.org/W2898782527","doi":"https://doi.org/10.1145/3232231","title":"Characterizing User Skills from Application Usage Traces with Hierarchical Attention Recurrent Networks","display_name":"Characterizing User Skills from Application Usage Traces with Hierarchical Attention Recurrent Networks","publication_year":2018,"publication_date":"2018-10-29","ids":{"openalex":"https://openalex.org/W2898782527","doi":"https://doi.org/10.1145/3232231","mag":"2898782527"},"language":"en","primary_location":{"id":"doi:10.1145/3232231","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3232231","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3232231","source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"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 Intelligent Systems and Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3232231","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057330200","display_name":"Longqi Yang","orcid":"https://orcid.org/0000-0002-6615-8615"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]},{"id":"https://openalex.org/I4405261073","display_name":"Cornell Tech","ror":"https://ror.org/04qscbg47","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295","https://openalex.org/I4405261073"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Longqi Yang","raw_affiliation_strings":["Cornell Tech, Cornell University, New York, NY"],"raw_orcid":"https://orcid.org/0000-0002-6615-8615","affiliations":[{"raw_affiliation_string":"Cornell Tech, Cornell University, New York, NY","institution_ids":["https://openalex.org/I205783295","https://openalex.org/I4405261073"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100400043","display_name":"Fang Chen","orcid":"https://orcid.org/0000-0003-4971-8729"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chen Fang","raw_affiliation_strings":["Adobe Research, Park Avenue, San Jose, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe Research, Park Avenue, San Jose, CA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109787260","display_name":"Hailin Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hailin Jin","raw_affiliation_strings":["Adobe Research, Park Avenue, San Jose, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe Research, Park Avenue, San Jose, CA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109851187","display_name":"Matthew D. Hoffman","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew D. Hoffman","raw_affiliation_strings":["Google, San Francisco, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google, San Francisco, CA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051587086","display_name":"Deborah Estrin","orcid":"https://orcid.org/0000-0001-6477-0096"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]},{"id":"https://openalex.org/I4405261073","display_name":"Cornell Tech","ror":"https://ror.org/04qscbg47","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295","https://openalex.org/I4405261073"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deborah Estrin","raw_affiliation_strings":["Cornell Tech, Cornell University, New York, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell Tech, Cornell University, New York, NY","institution_ids":["https://openalex.org/I205783295","https://openalex.org/I4405261073"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7465,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.80216207,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"9","issue":"6","first_page":"1","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9972000122070312,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9972000122070312,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9954000115394592,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9850999712944031,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8964766263961792},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.762276291847229},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6776254773139954},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5869568586349487},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5245464444160461},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.5038143992424011},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4935799837112427},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4136642813682556},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3581138849258423}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8964766263961792},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.762276291847229},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6776254773139954},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5869568586349487},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5245464444160461},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.5038143992424011},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4935799837112427},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4136642813682556},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3581138849258423},{"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:10.1145/3232231","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3232231","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3232231","source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"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 Intelligent Systems and Technology","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3232231","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3232231","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3232231","source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"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 Intelligent Systems and Technology","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7200000286102295,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G6683337051","display_name":"CHS: Medium: Immersive Recommendation Systems: User-Centric Recommendation Models and Applications","funder_award_id":"1700832","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306139","display_name":"Robert Wood Johnson Foundation","ror":"https://ror.org/02ymmdj85"},{"id":"https://openalex.org/F4320307765","display_name":"Pfizer","ror":"https://ror.org/01xdqrp08"},{"id":"https://openalex.org/F4320307786","display_name":"Adobe Systems","ror":"https://ror.org/059tvcg64"},{"id":"https://openalex.org/F4320318127","display_name":"UnitedHealth Group","ror":"https://ror.org/04a8rt780"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2898782527.pdf","grobid_xml":"https://content.openalex.org/works/W2898782527.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W6818085","https://openalex.org/W1485330246","https://openalex.org/W1522301498","https://openalex.org/W1678356000","https://openalex.org/W1895577753","https://openalex.org/W1928061009","https://openalex.org/W1966479322","https://openalex.org/W1981033071","https://openalex.org/W2046989307","https://openalex.org/W2047221353","https://openalex.org/W2048968070","https://openalex.org/W2050744589","https://openalex.org/W2064675550","https://openalex.org/W2066912131","https://openalex.org/W2068289206","https://openalex.org/W2071693280","https://openalex.org/W2089825482","https://openalex.org/W2095705004","https://openalex.org/W2105177883","https://openalex.org/W2106177900","https://openalex.org/W2122467011","https://openalex.org/W2124994029","https://openalex.org/W2125682643","https://openalex.org/W2131774270","https://openalex.org/W2133564696","https://openalex.org/W2134344734","https://openalex.org/W2136891251","https://openalex.org/W2140619391","https://openalex.org/W2143612262","https://openalex.org/W2149427297","https://openalex.org/W2153635508","https://openalex.org/W2157163421","https://openalex.org/W2162646781","https://openalex.org/W2168298345","https://openalex.org/W2271840356","https://openalex.org/W2465742202","https://openalex.org/W2470673105","https://openalex.org/W2577748531","https://openalex.org/W2583674722","https://openalex.org/W2587973414","https://openalex.org/W2612658537","https://openalex.org/W2618530766","https://openalex.org/W2734755249","https://openalex.org/W2768348081","https://openalex.org/W2949888546","https://openalex.org/W2950133940","https://openalex.org/W2963001778","https://openalex.org/W2963918631","https://openalex.org/W3099726625","https://openalex.org/W4242616095","https://openalex.org/W4291893431","https://openalex.org/W4301213493"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2521627374"],"abstract_inverted_index":{"Predicting":[0],"users\u2019":[1,22],"proficiencies":[2],"is":[3,55,109,166],"a":[4,14,33,100,119],"critical":[5],"component":[6],"of":[7,114],"AI-powered":[8],"personal":[9],"assistants.":[10],"This":[11],"article":[12],"introduces":[13],"novel":[15,34],"approach":[16,165],"for":[17],"the":[18,60,81,106,112,115,158],"prediction":[19],"based":[20],"on":[21],"diverse,":[23],"noisy,":[24],"and":[25,47,64,70,118,150],"passively":[26],"generated":[27],"application":[28],"usage":[29,128],"histories.":[30],"We":[31,86],"propose":[32],"bi-directional":[35],"recurrent":[36],"neural":[37],"network":[38],"with":[39,90],"hierarchical":[40],"attention":[41],"mechanism":[42],"to":[43,57,59,66,140,169],"extract":[44],"sequential":[45,83,151],"patterns":[46],"distinguish":[48],"informative":[49],"traces":[50],"from":[51,96],"noise.":[52],"Our":[53],"model":[54,89],"able":[56],"attend":[58],"most":[61],"discriminative":[62],"actions":[63],"sessions":[65],"make":[67],"more":[68],"accurate":[69],"directly":[71],"interpretable":[72],"predictions":[73],"while":[74],"requiring":[75],"50\u00d7":[76],"less":[77],"training":[78],"data":[79],"than":[80],"state-of-the-art":[82],"learning":[84,144],"approach.":[85],"evaluate":[87],"our":[88,135],"two":[91],"large":[92],"scale":[93],"datasets":[94],"collected":[95],"68K":[97],"Photoshop":[98],"users:":[99],"digital":[101],"design":[102],"skill":[103,108,121,129],"dataset":[104,122],"where":[105,123],"user":[107,142,173],"determined":[110],"by":[111],"quality":[113],"end":[116],"products":[117],"software":[120,127],"users":[124],"self-disclose":[125],"their":[126],"levels.":[130],"The":[131,163],"empirical":[132],"results":[133],"demonstrate":[134],"model\u2019s":[136,159],"superior":[137],"performance":[138],"compared":[139],"existing":[141],"representation":[143],"techniques":[145],"that":[146,171],"leverage":[147],"action":[148],"frequencies":[149],"patterns.":[152],"In":[153],"addition,":[154],"we":[155],"qualitatively":[156],"illustrate":[157],"significant":[160],"interpretative":[161],"power.":[162],"proposed":[164],"broadly":[167],"relevant":[168],"applications":[170],"generate":[172],"time-series":[174],"analytics.":[175]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2025-10-10T00:00:00"}
