{"id":"https://openalex.org/W2949704773","doi":"https://doi.org/10.1145/3292500.3330869","title":"Adversarial Substructured Representation Learning for Mobile User Profiling","display_name":"Adversarial Substructured Representation Learning for Mobile User Profiling","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2949704773","doi":"https://doi.org/10.1145/3292500.3330869","mag":"2949704773"},"language":"en","primary_location":{"id":"doi:10.1145/3292500.3330869","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3292500.3330869","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3330869","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3330869","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036270316","display_name":"Pengyang Wang","orcid":"https://orcid.org/0000-0003-3961-5523"},"institutions":[{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pengyang Wang","raw_affiliation_strings":["Missouri University of Science and Technology, Rolla, MO, USA"],"affiliations":[{"raw_affiliation_string":"Missouri University of Science and Technology, Rolla, MO, USA","institution_ids":["https://openalex.org/I20382870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032187620","display_name":"Yanjie Fu","orcid":"https://orcid.org/0000-0002-1767-8024"},"institutions":[{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanjie Fu","raw_affiliation_strings":["Missouri University of Science and Technology, Rolla, MO, USA"],"affiliations":[{"raw_affiliation_string":"Missouri University of Science and Technology, Rolla, MO, USA","institution_ids":["https://openalex.org/I20382870"]}]},{"author_position":"middle","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, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Rutgers University, Newark, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100353796","display_name":"Xiaolin Li","orcid":"https://orcid.org/0000-0002-0997-2776"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolin Li","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5036270316"],"corresponding_institution_ids":["https://openalex.org/I20382870"],"apc_list":null,"apc_paid":null,"fwci":15.8556,"has_fulltext":true,"cited_by_count":63,"citation_normalized_percentile":{"value":0.98994982,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"130","last_page":"138"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9932000041007996,"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":0.9932000041007996,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9897000193595886,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"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":0.7420921921730042},{"id":"https://openalex.org/keywords/profiling","display_name":"Profiling (computer programming)","score":0.6483630537986755},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5291795134544373},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5036410689353943},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4829546809196472},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4289966821670532},{"id":"https://openalex.org/keywords/substructure","display_name":"Substructure","score":0.42601513862609863},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4017457962036133},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.33133670687675476},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09972342848777771},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.09375321865081787}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7420921921730042},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.6483630537986755},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5291795134544373},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5036410689353943},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4829546809196472},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4289966821670532},{"id":"https://openalex.org/C99679407","wikidata":"https://www.wikidata.org/wiki/Q56761637","display_name":"Substructure","level":2,"score":0.42601513862609863},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4017457962036133},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.33133670687675476},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09972342848777771},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.09375321865081787},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3292500.3330869","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3292500.3330869","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3330869","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3292500.3330869","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3292500.3330869","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3330869","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G197654927","display_name":null,"funder_award_id":"1755946,IIS-1814510","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5874418566","display_name":"III: Small: Collaborative Research: A Multi-source Data Driven Optimization Framework for Inter-connected Express Delivery System Design and Inventory Rebalance","funder_award_id":"1814510","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7560220637","display_name":null,"funder_award_id":"IIS-1814510","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2949704773.pdf","grobid_xml":"https://content.openalex.org/works/W2949704773.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W189596042","https://openalex.org/W1888005072","https://openalex.org/W1983334819","https://openalex.org/W1992699579","https://openalex.org/W2004234600","https://openalex.org/W2071702404","https://openalex.org/W2079459186","https://openalex.org/W2088609771","https://openalex.org/W2099471712","https://openalex.org/W2102409316","https://openalex.org/W2109608387","https://openalex.org/W2110798204","https://openalex.org/W2115613106","https://openalex.org/W2125389028","https://openalex.org/W2144354855","https://openalex.org/W2153579005","https://openalex.org/W2154851992","https://openalex.org/W2160142299","https://openalex.org/W2173520492","https://openalex.org/W2187547424","https://openalex.org/W2202109488","https://openalex.org/W2271350114","https://openalex.org/W2340502990","https://openalex.org/W2393319904","https://openalex.org/W2419501139","https://openalex.org/W2434741482","https://openalex.org/W2465017405","https://openalex.org/W2512971201","https://openalex.org/W2557449848","https://openalex.org/W2567312369","https://openalex.org/W2604592713","https://openalex.org/W2608862709","https://openalex.org/W2727187776","https://openalex.org/W2743969099","https://openalex.org/W2757544304","https://openalex.org/W2768532803","https://openalex.org/W2802983566","https://openalex.org/W2803304669","https://openalex.org/W2807954821","https://openalex.org/W2808766325","https://openalex.org/W2808987817","https://openalex.org/W2890139949","https://openalex.org/W2901188091","https://openalex.org/W2903883820","https://openalex.org/W2904403013","https://openalex.org/W2951523806","https://openalex.org/W2963073614","https://openalex.org/W2963470893","https://openalex.org/W3104097132","https://openalex.org/W3105705953","https://openalex.org/W4299828299"],"related_works":["https://openalex.org/W3153444835","https://openalex.org/W2153916713","https://openalex.org/W2023846184","https://openalex.org/W2703419385","https://openalex.org/W2329056228","https://openalex.org/W2284584236","https://openalex.org/W2502115930","https://openalex.org/W2950955148","https://openalex.org/W1979083399","https://openalex.org/W2344320748"],"abstract_inverted_index":{"Mobile":[0,12],"user":[1,13,36,94,107,116],"profiles":[2],"are":[3],"a":[4,18,76,79,82,93,110,122,175,192,204,220],"summary":[5],"of":[6,8,48,62,92,112,145,160,186,212,242,250,270,289],"characteristics":[7],"user-specific":[9],"mobile":[10,25,35,63,106],"activities.":[11],"profiling":[14,65,108],"is":[15,81,88,140,150,164,181,189,236],"to":[16,99,141,182,228,237,246,284],"extract":[17],"user's":[19],"interest":[20],"and":[21,85,174,207],"behavioral":[22,26,52,117],"patterns":[23],"from":[24,115],"data.":[27,69],"While":[28],"some":[29],"efforts":[30],"have":[31],"been":[32],"made":[33],"for":[34,128,260,272],"profiling,":[37],"existing":[38],"methods":[39],"can":[40],"be":[41],"improved":[42,287],"via":[43],"representation":[44,113],"learning":[45,114,126],"with":[46,66],"awareness":[47],"substructures":[49],"in":[50,55],"users'":[51],"graphs.":[53,118],"Specifically,":[54],"this":[56,71,201],"paper,":[57],"we":[58,73,218,255,265,279],"study":[59],"the":[60,89,129,143,146,158,161,184,226,239,243,247,251,261,267,273,286,290],"problem":[61],"users":[64,271],"POI":[67,83,97],"check-in":[68],"To":[70],"end,":[72],"first":[74,138],"construct":[75],"graph,":[77,148],"where":[78],"vertex":[80],"category":[84],"an":[86,153,171,208,257],"edge":[87],"transition":[90],"frequency":[91],"between":[95,170],"two":[96,134],"categories,":[98],"represent":[100],"each":[101],"user.":[102],"We":[103,119],"then":[104],"formulate":[105],"as":[109,152,191,225],"task":[111],"later":[120],"develop":[121],"deep":[123],"adversarial":[124,196,209,234],"substructured":[125],"framework":[127,132],"task.":[130],"This":[131],"has":[133],"mutually-enhanced":[135],"components.":[136],"The":[137,178,233],"component":[139,180],"preserve":[142,183],"structure":[144,159,185],"entire":[147,162],"which":[149,188],"formulated":[151,190],"encoding-decoding":[154],"paradigm.":[155,198],"In":[156,199],"particular,":[157,200],"graph":[163,173,245],"preserved":[165],"by":[166],"minimizing":[167],"reconstruction":[168],"loss":[169],"original":[172,252],"reconstructed":[176,244],"graph.":[177,253],"second":[179],"subgraphs,":[187],"substructure":[193,205,215,241,249],"detector":[194,206,227],"based":[195],"training":[197],"paradigm":[202],"includes":[203],"trainer.":[210],"Instead":[211],"using":[213],"non-differentiable":[214],"detection":[216,231],"algorithms,":[217],"pre-train":[219],"differentiable":[221],"convolutional":[222],"neural":[223],"network":[224],"approximate":[229],"these":[230],"algorithms.":[232],"trainer":[235],"match":[238],"detected":[240,248],"Also,":[254],"provide":[256],"effective":[258],"solution":[259],"optimization":[262],"problems.":[263],"Moreover,":[264],"exploit":[266],"learned":[268],"representations":[269],"next":[274],"activity":[275],"type":[276],"prediction.":[277],"Finally,":[278],"present":[280],"extensive":[281],"experimental":[282],"results":[283],"demonstrate":[285],"performances":[288],"proposed":[291],"method.":[292]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":2}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
