{"id":"https://openalex.org/W4318812521","doi":"https://doi.org/10.1109/icdm54844.2022.00032","title":"Kernel-based Substructure Exploration for Next POI Recommendation","display_name":"Kernel-based Substructure Exploration for Next POI Recommendation","publication_year":2022,"publication_date":"2022-11-01","ids":{"openalex":"https://openalex.org/W4318812521","doi":"https://doi.org/10.1109/icdm54844.2022.00032"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm54844.2022.00032","pdf_url":null,"source":{"id":"https://openalex.org/S4363608061","display_name":"2021 IEEE International Conference on Data Mining (ICDM)","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://arxiv.org/pdf/2210.03969","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018666299","display_name":"Wei Ju","orcid":"https://orcid.org/0000-0001-9657-951X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Ju","raw_affiliation_strings":["School of Computer Science, Peking University, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058440014","display_name":"Yifang Qin","orcid":"https://orcid.org/0000-0002-7520-8039"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifang Qin","raw_affiliation_strings":["School of EECS, Peking University, China"],"affiliations":[{"raw_affiliation_string":"School of EECS, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009278730","display_name":"Ziyue Qiao","orcid":null},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Ziyue Qiao","raw_affiliation_strings":["Artificial Intelligence Thrust, The Hong Kong University of Science and Technology, (Guangzhou), China"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Thrust, The Hong Kong University of Science and Technology, (Guangzhou), China","institution_ids":["https://openalex.org/I200769079","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100426938","display_name":"Xiao Luo","orcid":"https://orcid.org/0000-0002-7987-3714"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Luo","raw_affiliation_strings":["School of Mathematical Sciences, Peking University, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100398556","display_name":"Yifan Wang","orcid":"https://orcid.org/0000-0002-2933-6363"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Wang","raw_affiliation_strings":["School of Computer Science, Peking University, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"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/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanjie Fu","raw_affiliation_strings":["Department of Computer Science, University of Central Florida, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Central Florida, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100642537","display_name":"Ming Zhang","orcid":"https://orcid.org/0000-0002-9809-3430"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Zhang","raw_affiliation_strings":["School of Computer Science, Peking University, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institution_assertions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.201,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.99968,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"221","last_page":"230"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9999,"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":0.9999,"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":0.9927,"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":0.97,"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/leverage","display_name":"Leverage (statistics)","score":0.74019825},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.4737975},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.44000864},{"id":"https://openalex.org/keywords/point-of-interest","display_name":"Point of interest","score":0.43274266}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.81196743},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.74019825},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4830392},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.4737975},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4674151},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4547164},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.44000864},{"id":"https://openalex.org/C150140777","wikidata":"https://www.wikidata.org/wiki/Q960648","display_name":"Point of interest","level":2,"score":0.43274266},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4199692},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4084074},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40225822},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35515326},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32192302},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm54844.2022.00032","pdf_url":null,"source":{"id":"https://openalex.org/S4363608061","display_name":"2021 IEEE International Conference on Data Mining (ICDM)","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.03969","pdf_url":"http://arxiv.org/pdf/2210.03969","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.03969","pdf_url":"http://arxiv.org/pdf/2210.03969","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":null},{"funder":"https://openalex.org/F4320337504","funder_display_name":"Research and Development","award_id":null}],"datasets":[],"versions":[],"referenced_works_count":35,"referenced_works":["https://openalex.org/W1816257748","https://openalex.org/W2017921654","https://openalex.org/W2070915285","https://openalex.org/W2071702404","https://openalex.org/W2142498761","https://openalex.org/W2147286743","https://openalex.org/W2171279286","https://openalex.org/W2584122106","https://openalex.org/W2602753196","https://openalex.org/W2723293840","https://openalex.org/W2788114581","https://openalex.org/W2798749602","https://openalex.org/W2808111827","https://openalex.org/W2907639449","https://openalex.org/W2962745591","https://openalex.org/W2998167534","https://openalex.org/W3040157551","https://openalex.org/W3045200674","https://openalex.org/W3100278010","https://openalex.org/W3100561866","https://openalex.org/W3101707147","https://openalex.org/W3129017148","https://openalex.org/W3164797320","https://openalex.org/W3170553237","https://openalex.org/W3172429379","https://openalex.org/W3203589076","https://openalex.org/W3204669985","https://openalex.org/W3208876695","https://openalex.org/W4205551258","https://openalex.org/W4213457653","https://openalex.org/W4225338086","https://openalex.org/W4226058932","https://openalex.org/W4281563651","https://openalex.org/W4282913028","https://openalex.org/W4289533979"],"related_works":["https://openalex.org/W3023581765","https://openalex.org/W2968745142","https://openalex.org/W2910664707","https://openalex.org/W2809363009","https://openalex.org/W2499363748","https://openalex.org/W2368095327","https://openalex.org/W2350747448","https://openalex.org/W2348159088","https://openalex.org/W2060018053","https://openalex.org/W2045871438"],"abstract_inverted_index":{"Point-of-Interest":[0],"(POI)":[1],"recommendation,":[2,99],"which":[3,100],"benefits":[4],"from":[5,185],"the":[6,30,63,85,102,125,142,147,156,192,212,220],"proliferation":[7],"of":[8,104,116,215],"GPS-enabled":[9],"devices":[10],"and":[11,43,107,120,133,181],"location-based":[12],"social":[13],"networks":[14,54],"(LBSNs),":[15],"plays":[16],"an":[17],"increasingly":[18],"important":[19],"role":[20],"in":[21,110,155],"recommender":[22],"systems.":[23],"It":[24],"aims":[25],"to":[26,32,37,56,78,140,166,177,198],"provide":[27],"users":[28],"with":[29],"convenience":[31],"discover":[33],"their":[34],"interested":[35],"places":[36],"visit":[38],"based":[39],"on":[40,206],"previous":[41],"visits":[42],"current":[44],"status.":[45],"Most":[46],"existing":[47],"methods":[48,66],"usually":[49],"merely":[50],"leverage":[51,134],"recurrent":[52],"neural":[53,138,164],"(RNNs)":[55],"explore":[57,151],"sequential":[58,81,108,122,153,158,182],"influences":[59,72,109],"for":[60,96],"recommendation.":[61],"Despite":[62],"effectiveness,":[64],"these":[65],"not":[67],"only":[68],"neglect":[69],"topological":[70,143],"geographical":[71,106,118,131,144,180],"among":[73],"POIs,":[74],"but":[75],"also":[76],"fail":[77],"model":[79],"high-order":[80,152],"substructures.":[82],"To":[83],"tackle":[84],"above":[86],"issues,":[87],"we":[88,128,150],"propose":[89],"a":[90,111,117,121,130,135,161,171],"Kernel-Based":[91],"Graph":[92],"Neural":[93],"Network":[94],"(KBGNN)":[95],"next":[97],"POI":[98],"combines":[101],"characteristics":[103],"both":[105],"collaborative":[112],"way.":[113],"KBGNN":[114],"consists":[115],"module":[119],"module.":[123],"On":[124,146],"one":[126],"hand,":[127,149],"construct":[129],"graph":[132,159,162],"message":[136],"passing":[137],"network":[139,165],"capture":[141,167],"influences.":[145],"other":[148],"substructures":[154],"user-aware":[157],"using":[160],"kernel":[163],"user":[168],"preferences.":[169],"Finally,":[170],"consistency":[172],"learning":[173],"framework":[174],"is":[175],"introduced":[176],"jointly":[178],"incorporate":[179],"information":[183],"extracted":[184],"two":[186,193,207],"separate":[187],"graphs.":[188],"In":[189],"this":[190],"way,":[191],"modules":[194],"effectively":[195],"exchange":[196],"knowledge":[197],"mutually":[199],"enhance":[200],"each":[201],"other.":[202],"Extensive":[203],"experiments":[204],"conducted":[205],"real-world":[208],"LBSN":[209],"datasets":[210],"demonstrate":[211],"superior":[213],"performance":[214],"our":[216],"proposed":[217],"method":[218],"over":[219],"state-of-the-arts.":[221],"Our":[222],"codes":[223],"are":[224],"available":[225],"at":[226],"https://github.com/":[227],"ang6ang/KBGNN.":[228]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4318812521","counts_by_year":[{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1}],"updated_date":"2025-01-05T12:44:10.341578","created_date":"2023-02-02"}