{"id":"https://openalex.org/W3007135535","doi":"https://doi.org/10.3390/ijgi9020113","title":"A Spatiotemporal Dilated Convolutional Generative Network for Point-Of-Interest Recommendation","display_name":"A Spatiotemporal Dilated Convolutional Generative Network for Point-Of-Interest Recommendation","publication_year":2020,"publication_date":"2020-02-19","ids":{"openalex":"https://openalex.org/W3007135535","doi":"https://doi.org/10.3390/ijgi9020113","mag":"3007135535"},"language":"en","primary_location":{"id":"doi:10.3390/ijgi9020113","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi9020113","pdf_url":"https://www.mdpi.com/2220-9964/9/2/113/pdf?version=1583053763","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2220-9964/9/2/113/pdf?version=1583053763","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101474600","display_name":"Chunyang Liu","orcid":"https://orcid.org/0000-0002-3694-0075"},"institutions":[{"id":"https://openalex.org/I184681353","display_name":"Anhui University of Science and Technology","ror":"https://ror.org/00q9atg80","country_code":"CN","type":"education","lineage":["https://openalex.org/I184681353"]},{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunyang Liu","raw_affiliation_strings":["School of Environment Science and Spatial Informatics, China University of Mining and Technology (CUMT), Xuzhou 221116, China","School of Geodesy and Geomatics, Anhui University of Science and Technology, Huainan 232001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Environment Science and Spatial Informatics, China University of Mining and Technology (CUMT), Xuzhou 221116, China","institution_ids":["https://openalex.org/I25757504"]},{"raw_affiliation_string":"School of Geodesy and Geomatics, Anhui University of Science and Technology, Huainan 232001, China","institution_ids":["https://openalex.org/I184681353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109448683","display_name":"Jiping Liu","orcid":"https://orcid.org/0000-0001-9275-3250"},"institutions":[{"id":"https://openalex.org/I4210114963","display_name":"Chinese Academy of Surveying and Mapping","ror":"https://ror.org/02j693n47","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114963"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiping Liu","raw_affiliation_strings":["Chinese Academy of Surveying and Mapping, Beijing 100830, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Surveying and Mapping, Beijing 100830, China","institution_ids":["https://openalex.org/I4210114963"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100716244","display_name":"Shenghua Xu","orcid":"https://orcid.org/0000-0001-9275-3250"},"institutions":[{"id":"https://openalex.org/I4210114963","display_name":"Chinese Academy of Surveying and Mapping","ror":"https://ror.org/02j693n47","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114963"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shenghua Xu","raw_affiliation_strings":["Chinese Academy of Surveying and Mapping, Beijing 100830, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Surveying and Mapping, Beijing 100830, China","institution_ids":["https://openalex.org/I4210114963"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100370411","display_name":"Jian Wang","orcid":"https://orcid.org/0000-0002-1559-9314"},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wang","raw_affiliation_strings":["School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 100044, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 100044, China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039318614","display_name":"Chao Liu","orcid":"https://orcid.org/0000-0001-9217-3256"},"institutions":[{"id":"https://openalex.org/I184681353","display_name":"Anhui University of Science and Technology","ror":"https://ror.org/00q9atg80","country_code":"CN","type":"education","lineage":["https://openalex.org/I184681353"]},{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Liu","raw_affiliation_strings":["School of Environment Science and Spatial Informatics, China University of Mining and Technology (CUMT), Xuzhou 221116, China","School of Geodesy and Geomatics, Anhui University of Science and Technology, Huainan 232001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Environment Science and Spatial Informatics, China University of Mining and Technology (CUMT), Xuzhou 221116, China","institution_ids":["https://openalex.org/I25757504"]},{"raw_affiliation_string":"School of Geodesy and Geomatics, Anhui University of Science and Technology, Huainan 232001, China","institution_ids":["https://openalex.org/I184681353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101808017","display_name":"Tianyang Chen","orcid":"https://orcid.org/0000-0002-6714-3159"},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianyang Chen","raw_affiliation_strings":["Department of Geography and Earth Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography and Earth Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA","institution_ids":["https://openalex.org/I102149020"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100648261","display_name":"Tao Jiang","orcid":"https://orcid.org/0000-0001-8296-3027"},"institutions":[{"id":"https://openalex.org/I4210114963","display_name":"Chinese Academy of Surveying and Mapping","ror":"https://ror.org/02j693n47","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114963"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Jiang","raw_affiliation_strings":["Chinese Academy of Surveying and Mapping, Beijing 100830, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Surveying and Mapping, Beijing 100830, China","institution_ids":["https://openalex.org/I4210114963"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5109448683"],"corresponding_institution_ids":["https://openalex.org/I4210114963"],"apc_list":{"value":1700,"currency":"CHF","value_usd":1893},"apc_paid":{"value":1700,"currency":"CHF","value_usd":1893},"fwci":3.0766,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.92975988,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"9","issue":"2","first_page":"113","last_page":"113"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9840999841690063,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9800000190734863,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8087282180786133},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6411235332489014},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5833340883255005},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5805378556251526},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5295354127883911},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.4977298080921173},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4556160569190979},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.42405885457992554},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.415131539106369},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3948417901992798},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34857261180877686},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.33163025975227356},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.26894816756248474}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8087282180786133},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6411235332489014},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5833340883255005},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5805378556251526},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5295354127883911},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.4977298080921173},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4556160569190979},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.42405885457992554},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.415131539106369},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3948417901992798},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34857261180877686},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.33163025975227356},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26894816756248474},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/ijgi9020113","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi9020113","pdf_url":"https://www.mdpi.com/2220-9964/9/2/113/pdf?version=1583053763","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9f9869cae27349228d633b009f08f4d9","is_oa":true,"landing_page_url":"https://doaj.org/article/9f9869cae27349228d633b009f08f4d9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISPRS International Journal of Geo-Information, Vol 9, Iss 2, p 113 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2220-9964/9/2/113/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/ijgi9020113","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/ijgi9020113","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi9020113","pdf_url":"https://www.mdpi.com/2220-9964/9/2/113/pdf?version=1583053763","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3007135535.pdf"},"referenced_works_count":61,"referenced_works":["https://openalex.org/W1546409232","https://openalex.org/W1665214252","https://openalex.org/W1972243012","https://openalex.org/W1973749534","https://openalex.org/W1984189333","https://openalex.org/W1986050033","https://openalex.org/W2003684386","https://openalex.org/W2017921654","https://openalex.org/W2021504710","https://openalex.org/W2044672016","https://openalex.org/W2070075246","https://openalex.org/W2071702404","https://openalex.org/W2073013176","https://openalex.org/W2087692915","https://openalex.org/W2100664567","https://openalex.org/W2125761757","https://openalex.org/W2140310134","https://openalex.org/W2147489358","https://openalex.org/W2153579005","https://openalex.org/W2157331557","https://openalex.org/W2160815625","https://openalex.org/W2163605009","https://openalex.org/W2184045248","https://openalex.org/W2193413348","https://openalex.org/W2194775991","https://openalex.org/W2205235818","https://openalex.org/W2394103513","https://openalex.org/W2408538552","https://openalex.org/W2539781657","https://openalex.org/W2573719245","https://openalex.org/W2588323309","https://openalex.org/W2604411573","https://openalex.org/W2604438604","https://openalex.org/W2618530766","https://openalex.org/W2735269983","https://openalex.org/W2739273093","https://openalex.org/W2770823020","https://openalex.org/W2783272285","https://openalex.org/W2788114581","https://openalex.org/W2795684330","https://openalex.org/W2801183026","https://openalex.org/W2807855639","https://openalex.org/W2808008183","https://openalex.org/W2808425487","https://openalex.org/W2898621004","https://openalex.org/W2902040508","https://openalex.org/W2905432015","https://openalex.org/W2925561576","https://openalex.org/W2947144452","https://openalex.org/W2949382160","https://openalex.org/W2949987098","https://openalex.org/W2950133940","https://openalex.org/W2950344723","https://openalex.org/W2950635152","https://openalex.org/W2953318193","https://openalex.org/W2968758246","https://openalex.org/W3122507327","https://openalex.org/W6668440036","https://openalex.org/W6684191040","https://openalex.org/W6741719136","https://openalex.org/W7075339643"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W2280377497","https://openalex.org/W4387506531","https://openalex.org/W4238433571","https://openalex.org/W3174044702","https://openalex.org/W2967848559","https://openalex.org/W4283803360"],"abstract_inverted_index":{"With":[0],"the":[1,21,40,58,84,120,146,224,242,256],"growing":[2],"popularity":[3],"of":[4,83,158,190],"location-based":[5],"social":[6],"media":[7],"applications,":[8],"point-of-interest":[9],"(POI)":[10],"recommendation":[11,42,113,232,258],"has":[12],"become":[13],"important":[14],"in":[15,57,74,114,196,201,239,255],"recent":[16],"years.":[17],"Several":[18],"techniques,":[19],"especially":[20],"collaborative":[22],"filtering":[23],"(CF),":[24],"Markov":[25],"chain":[26],"(MC),":[27],"and":[28,47,67,150,163,180,199,218,234,240],"recurrent":[29,63],"neural":[30,64],"network":[31,109,135],"(RNN)":[32],"based":[33],"methods,":[34],"have":[35,70],"been":[36,71],"recently":[37],"proposed":[38,225,246],"for":[39,111,230],"POI":[41,75,112,140,231,257],"service.":[43],"However,":[44],"CF-based":[45],"methods":[46,49],"MC-based":[48],"are":[50],"ineffective":[51],"to":[52,139,170,181],"represent":[53],"complicated":[54,148],"interaction":[55],"relations":[56],"historical":[59],"check-in":[60,95,152,243],"sequences.":[61,244],"Although":[62],"networks":[65],"(RNNs)":[66],"its":[68],"variants":[69],"successfully":[72],"employed":[73],"recommendation,":[76,141],"they":[77],"depend":[78],"on":[79],"a":[80,94,104,127,137,156,197,202],"hidden":[81],"state":[82],"entire":[85],"past":[86],"that":[87,223],"cannot":[88],"fully":[89],"utilize":[90],"parallel":[91],"computation":[92],"within":[93],"sequence.":[96],"To":[97],"address":[98],"these":[99],"above":[100],"limitations,":[101],"we":[102,125,168,205],"propose":[103,169],"spatiotemporal":[105],"dilated":[106,132,159],"convolutional":[107,133],"generative":[108,134],"(ST-DCGN)":[110],"this":[115],"study.":[116],"Firstly,":[117],"inspired":[118],"by":[119,154,175,186],"Google":[121],"DeepMind\u2019":[122],"WaveNet":[123],"model,":[124],"introduce":[126],"simple":[128],"but":[129],"very":[130],"effective":[131],"as":[136],"solution":[138],"which":[142],"can":[143,235],"efficiently":[144],"model":[145,227,247],"user\u2019s":[147,172,183],"short-":[149],"long-range":[151],"sequence":[153],"using":[155,211],"stack":[157],"causal":[160],"convolution":[161],"layers":[162],"residual":[164],"block":[165],"structure.":[166],"Then,":[167],"acquire":[171],"spatial":[173],"preference":[174,185],"modeling":[176],"continuous":[177],"geographical":[178],"distances,":[179],"capture":[182],"temporal":[184],"considering":[187],"two":[188,212],"types":[189],"time":[191,254],"periodic":[192],"patterns":[193],"(i.e.,":[194],"hours":[195],"day":[198],"days":[200],"week).":[203],"Moreover,":[204],"conducted":[206],"an":[207],"extensive":[208],"performance":[209],"evaluation":[210],"large-scale":[213],"real-world":[214],"datasets,":[215],"namely":[216],"Foursquare":[217],"Instagram.":[219],"Experimental":[220],"results":[221],"show":[222],"ST-DCGN":[226],"is":[228],"well-suited":[229],"problems":[233],"effectively":[236],"learn":[237],"dependencies":[238],"between":[241],"The":[245],"attains":[248],"state-of-the-art":[249],"accuracy":[250],"with":[251],"less":[252],"training":[253],"task.":[259]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2020-03-06T00:00:00"}