{"id":"https://openalex.org/W3215033458","doi":"https://doi.org/10.1145/3485631","title":"STARec: Adaptive Learning with Spatiotemporal and Activity Influence for POI Recommendation","display_name":"STARec: Adaptive Learning with Spatiotemporal and Activity Influence for POI Recommendation","publication_year":2021,"publication_date":"2021-11-29","ids":{"openalex":"https://openalex.org/W3215033458","doi":"https://doi.org/10.1145/3485631","mag":"3215033458"},"language":"en","primary_location":{"id":"doi:10.1145/3485631","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485631","pdf_url":null,"source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069003605","display_name":"Weiyu Ji","orcid":"https://orcid.org/0000-0002-5696-0364"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weiyu Ji","raw_affiliation_strings":["School of Computer Science (National Pilot Software Engineering School) & Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Haidian District, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5696-0364","affiliations":[{"raw_affiliation_string":"School of Computer Science (National Pilot Software Engineering School) & Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Haidian District, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xiangwu Meng","orcid":"https://orcid.org/0000-0003-2180-5986"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangwu Meng","raw_affiliation_strings":["School of Computer Science (National Pilot Software Engineering School) & Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Haidian District, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2180-5986","affiliations":[{"raw_affiliation_string":"School of Computer Science (National Pilot Software Engineering School) & Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Haidian District, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101566112","display_name":"Yujie Zhang","orcid":"https://orcid.org/0000-0003-1805-8342"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujie Zhang","raw_affiliation_strings":["School of Computer Science (National Pilot Software Engineering School) & Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Haidian District, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1805-8342","affiliations":[{"raw_affiliation_string":"School of Computer Science (National Pilot Software Engineering School) & Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Haidian District, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5069003605"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":5.4102,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.95917329,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"40","issue":"4","first_page":"1","last_page":"40"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9837999939918518,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.982200026512146,"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":0.870661199092865},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7995378971099854},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6065177917480469},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5120263695716858},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.4961572587490082},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4814109802246094},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4654653072357178},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4573397934436798},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.42812949419021606},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4106558859348297},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.383718878030777},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33502697944641113},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.33368468284606934},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.1973128616809845}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.870661199092865},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7995378971099854},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6065177917480469},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5120263695716858},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.4961572587490082},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4814109802246094},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4654653072357178},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4573397934436798},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.42812949419021606},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4106558859348297},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.383718878030777},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33502697944641113},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33368468284606934},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.1973128616809845},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3485631","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485631","pdf_url":null,"source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.4699999988079071,"display_name":"Reduced inequalities"},{"id":"https://metadata.un.org/sdg/16","score":0.44999998807907104,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1609010894","https://openalex.org/W1880262756","https://openalex.org/W1967533108","https://openalex.org/W1984189333","https://openalex.org/W1995109099","https://openalex.org/W2009779426","https://openalex.org/W2032611833","https://openalex.org/W2052261215","https://openalex.org/W2055852858","https://openalex.org/W2062079386","https://openalex.org/W2064702560","https://openalex.org/W2072992969","https://openalex.org/W2073013176","https://openalex.org/W2074194940","https://openalex.org/W2087692915","https://openalex.org/W2109242993","https://openalex.org/W2136796925","https://openalex.org/W2139809240","https://openalex.org/W2141596757","https://openalex.org/W2150731624","https://openalex.org/W2250753706","https://openalex.org/W2434565296","https://openalex.org/W2444485119","https://openalex.org/W2501711337","https://openalex.org/W2531384334","https://openalex.org/W2534727297","https://openalex.org/W2566424107","https://openalex.org/W2584122106","https://openalex.org/W2604438604","https://openalex.org/W2626919702","https://openalex.org/W2643577078","https://openalex.org/W2750303327","https://openalex.org/W2758089162","https://openalex.org/W2783272285","https://openalex.org/W2783588057","https://openalex.org/W2793484810","https://openalex.org/W2808425487","https://openalex.org/W2900806287","https://openalex.org/W2907639449","https://openalex.org/W2914041468","https://openalex.org/W2921942806","https://openalex.org/W2922530940","https://openalex.org/W2923964967","https://openalex.org/W2924612058","https://openalex.org/W2947374734","https://openalex.org/W2963367478","https://openalex.org/W2963707260","https://openalex.org/W2981038821","https://openalex.org/W3012632375","https://openalex.org/W3014900199","https://openalex.org/W3043239945","https://openalex.org/W3065432481","https://openalex.org/W3080292238","https://openalex.org/W3093741743","https://openalex.org/W3099237846","https://openalex.org/W3102331315"],"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/W3174044702","https://openalex.org/W4238433571","https://openalex.org/W2967848559","https://openalex.org/W4283803360"],"abstract_inverted_index":{"POI":[0],"recommendation":[1,63,185],"has":[2],"become":[3],"an":[4,16],"essential":[5],"means":[6],"to":[7,26,109,132,159,188],"help":[8],"people":[9],"discover":[10],"attractive":[11],"places.":[12],"Intuitively,":[13],"activities":[14],"have":[15],"important":[17],"impact":[18,147],"on":[19,84,166],"users\u2019":[20,92,118],"decision-making,":[21],"because":[22,138],"users":[23],"select":[24],"POIs":[25],"attend":[27],"corresponding":[28,150],"activities.":[29],"However,":[30],"many":[31],"existing":[32],"studies":[33],"ignore":[34],"the":[35,69,85,115,145,174],"social":[36,86,93,119,136],"motivation":[37],"of":[38,71,88,139,149,183],"user":[39,50,58,106,112,135],"behaviors":[40],"and":[41,101,121,144,197],"regard":[42],"all":[43],"check-ins":[44],"as":[45,95],"influenced":[46],"only":[47],"by":[48],"individual":[49,99,105],"interests.":[51],"As":[52],"a":[53,76],"result,":[54],"they":[55],"cannot":[56],"model":[57,79,177],"preferences":[59,94,120,137],"accurately,":[60],"which":[61],"degrades":[62],"effectiveness.":[64],"In":[65],"this":[66,73],"article,":[67],"from":[68,97],"perspective":[70],"activities,":[72,89],"study":[74],"proposes":[75],"probabilistic":[77],"generative":[78],"called":[80],"STARec.":[81],"Specifically,":[82],"based":[83],"effect":[87],"STARec":[90,176],"defines":[91],"distinct":[96],"their":[98,122],"interests":[100,108],"combines":[102],"these":[103,143],"with":[104],"activity":[107,127],"effectively":[110],"depict":[111],"preferences.":[113],"Moreover,":[114],"inconsistency":[116],"between":[117,142],"decisions":[123],"is":[124,130],"modeled.":[125],"An":[126,152],"frequency":[128],"feature":[129],"introduced":[131],"acquire":[133],"accurate":[134],"close":[140],"correlation":[141],"key":[146],"factor":[148],"check-ins.":[151],"alias":[153],"sampling-based":[154],"training":[155],"method":[156],"was":[157],"used":[158],"accelerate":[160],"training.":[161],"Extensive":[162],"experiments":[163],"were":[164],"conducted":[165],"two":[167],"real-world":[168],"datasets.":[169],"Experimental":[170],"results":[171],"demonstrated":[172],"that":[173],"proposed":[175],"achieves":[178],"superior":[179],"performance":[180],"in":[181,192],"terms":[182],"high":[184],"accuracy,":[186],"robustness":[187],"data":[189],"sparsity,":[190],"effectiveness":[191],"handling":[193],"cold-start":[194],"problems,":[195],"efficiency,":[196],"interpretability.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}