{"id":"https://openalex.org/W4414165712","doi":"https://doi.org/10.1109/tsc.2025.3607918","title":"FedHGS: A Federated Point-of-Interest Recommendation Method Based on Heterogeneous Graph Semantics","display_name":"FedHGS: A Federated Point-of-Interest Recommendation Method Based on Heterogeneous Graph Semantics","publication_year":2025,"publication_date":"2025-09-09","ids":{"openalex":"https://openalex.org/W4414165712","doi":"https://doi.org/10.1109/tsc.2025.3607918"},"language":"en","primary_location":{"id":"doi:10.1109/tsc.2025.3607918","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsc.2025.3607918","pdf_url":null,"source":{"id":"https://openalex.org/S204223317","display_name":"IEEE Transactions on Services Computing","issn_l":"1939-1374","issn":["1939-1374","2372-0204"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Services Computing","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":null,"display_name":"Xunan Dong","orcid":"https://orcid.org/0009-0002-4692-3313"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xunan Dong","raw_affiliation_strings":["School of Big Data and Software Engineering, Chongqing University, Chongqing, China","School of big data and software engineering, Chongqing University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Big Data and Software Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"School of big data and software engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024752776","display_name":"Jun Zeng","orcid":"https://orcid.org/0000-0003-3129-9052"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zeng","raw_affiliation_strings":["School of Big Data and Software Engineering, Chongqing University, Chongqing, China","School of big data and software engineering, Chongqing University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Big Data and Software Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"School of big data and software engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052018461","display_name":"Lin Zhong","orcid":"https://orcid.org/0000-0002-7410-9020"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Zhong","raw_affiliation_strings":["School of Computer Science, Harbin Institute of Technology, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102842771","display_name":"Haoran Tang","orcid":"https://orcid.org/0000-0003-0700-8710"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Haoran Tang","raw_affiliation_strings":["Department of Computing, Hong Kong Polytechnic University, Hong Kong SAR, China","Department of Computing, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR"],"affiliations":[{"raw_affiliation_string":"Department of Computing, Hong Kong Polytechnic University, Hong Kong SAR, China","institution_ids":["https://openalex.org/I14243506"]},{"raw_affiliation_string":"Department of Computing, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024416196","display_name":"Junhao Wen","orcid":"https://orcid.org/0000-0002-6561-560X"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junhao Wen","raw_affiliation_strings":["School of Big Data and Software Engineering, Chongqing University, Chongqing, China","School of big data and software engineering, Chongqing University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Big Data and Software Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"School of big data and software engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002210013","display_name":"Min Gao","orcid":"https://orcid.org/0000-0003-0127-7477"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Gao","raw_affiliation_strings":["School of Big Data and Software Engineering, Chongqing University, Chongqing, China","School of big data and software engineering, Chongqing University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Big Data and Software Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"School of big data and software engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I158842170"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.35659496,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"6","first_page":"3780","last_page":"3793"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.968500018119812,"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":0.968500018119812,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9684000015258789,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9531999826431274,"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/personalization","display_name":"Personalization","score":0.676800012588501},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4991999864578247},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.45899999141693115},{"id":"https://openalex.org/keywords/semantic-heterogeneity","display_name":"Semantic heterogeneity","score":0.4564000070095062},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.453900009393692},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4117000102996826},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4018999934196472},{"id":"https://openalex.org/keywords/distributed-database","display_name":"Distributed database","score":0.3675999939441681},{"id":"https://openalex.org/keywords/user-profile","display_name":"User profile","score":0.3260999917984009}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8962000012397766},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.676800012588501},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4991999864578247},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.45899999141693115},{"id":"https://openalex.org/C2778180026","wikidata":"https://www.wikidata.org/wiki/Q18378163","display_name":"Semantic heterogeneity","level":4,"score":0.4564000070095062},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.453900009393692},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4117000102996826},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4027000069618225},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4018999934196472},{"id":"https://openalex.org/C70061542","wikidata":"https://www.wikidata.org/wiki/Q989016","display_name":"Distributed database","level":2,"score":0.3675999939441681},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35269999504089355},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.33809998631477356},{"id":"https://openalex.org/C2780150774","wikidata":"https://www.wikidata.org/wiki/Q252500","display_name":"User profile","level":2,"score":0.3260999917984009},{"id":"https://openalex.org/C67712803","wikidata":"https://www.wikidata.org/wiki/Q7901853","display_name":"User modeling","level":3,"score":0.3199999928474426},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3138999938964844},{"id":"https://openalex.org/C20136886","wikidata":"https://www.wikidata.org/wiki/Q749647","display_name":"Interoperability","level":2,"score":0.31349998712539673},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.3089999854564667},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.3050000071525574},{"id":"https://openalex.org/C138959212","wikidata":"https://www.wikidata.org/wiki/Q1806783","display_name":"Load balancing (electrical power)","level":3,"score":0.2978000044822693},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2939000129699707},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.2874999940395355},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C35578498","wikidata":"https://www.wikidata.org/wiki/Q193424","display_name":"Web service","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsc.2025.3607918","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsc.2025.3607918","pdf_url":null,"source":{"id":"https://openalex.org/S204223317","display_name":"IEEE Transactions on Services Computing","issn_l":"1939-1374","issn":["1939-1374","2372-0204"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Services Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8654101375","display_name":null,"funder_award_id":"CSTB2024NSCQ-MSX0617","funder_id":"https://openalex.org/F4320323172","funder_display_name":"Natural Science Foundation of Chongqing"}],"funders":[{"id":"https://openalex.org/F4320323172","display_name":"Natural Science Foundation of Chongqing","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2963367478","https://openalex.org/W3002265191","https://openalex.org/W3005071803","https://openalex.org/W3204874618","https://openalex.org/W3210126249","https://openalex.org/W4205316161","https://openalex.org/W4312221336","https://openalex.org/W4322576481","https://openalex.org/W4366203286","https://openalex.org/W4368232849","https://openalex.org/W4375798313","https://openalex.org/W4380091056","https://openalex.org/W4382463479","https://openalex.org/W4382654244","https://openalex.org/W4384655702","https://openalex.org/W4385583963","https://openalex.org/W4386473383","https://openalex.org/W4387846566","https://openalex.org/W4389664597","https://openalex.org/W4390357366","https://openalex.org/W4391528991","https://openalex.org/W4392940498","https://openalex.org/W4396712858","https://openalex.org/W4396758571","https://openalex.org/W4400447509","https://openalex.org/W4401107006","https://openalex.org/W4401863521","https://openalex.org/W4401863544","https://openalex.org/W4402260442","https://openalex.org/W4402896775","https://openalex.org/W4404871539","https://openalex.org/W4406264096","https://openalex.org/W4406316163","https://openalex.org/W4407316484","https://openalex.org/W4409012254","https://openalex.org/W4409149905"],"related_works":[],"abstract_inverted_index":{"Federated":[0],"point-of-interest":[1],"(POI)":[2],"recommendation":[3,47,146,205],"achieves":[4],"global":[5,124,134,203,216],"model":[6,86,109,185],"training":[7,13,193],"and":[8,99,127,163,188,197,217],"optimization":[9],"through":[10,176],"a":[11,58,143],"distributed":[12,35,59],"framework,":[14],"ensuring":[15],"that":[16],"user":[17,30,76,161,173],"data":[18,31,38,60,71,96],"is":[19,115],"always":[20],"stored":[21],"locally":[22],"on":[23,149],"the":[24,42,53,62,73,82,90,93,123,133,157,165,199,202,215],"client":[25,70],"side,":[26],"thereby":[27,80],"effectively":[28,118],"protecting":[29],"privacy.":[32],"However,":[33],"this":[34,120,140],"nature":[36],"of":[37,45,65,75,84,132,159,167,201,221],"also":[39],"severely":[40],"limits":[41],"performance":[43,131,200,219],"improvement":[44,83],"POI":[46,145,204],"models":[48,169],"under":[49],"federated":[50,144],"learning.":[51],"On":[52,89],"one":[54],"hand,":[55,92],"in":[56,68,95,107,129],"such":[57],"environment,":[61],"semantic":[63,179],"fragmentation":[64],"feature":[66],"spaces":[67],"local":[69,85,108,160,168,184,218],"hinders":[72],"learning":[74,171],"personalized":[77,172],"preference":[78,174],"representations,":[79],"limiting":[81],"personalization":[87,166],"performance.":[88],"other":[91],"heterogeneity":[94],"quantity,":[97],"quality,":[98],"distribution":[100],"among":[101],"clients":[102,196],"leads":[103],"to":[104,117,191,212],"significant":[105],"differences":[106,194],"training.The":[110],"traditional":[111],"average":[112],"aggregation":[113,125,190],"strategy":[114],"difficult":[116],"alleviate":[119],"difference,":[121],"affecting":[122],"efficiency":[126],"resulting":[128],"insufficient":[130],"model.":[135,206],"To":[136],"address":[137],"these":[138],"challenges,":[139],"paper":[141],"proposes":[142],"method":[147,155],"based":[148],"heterogeneous":[150,177],"graph":[151,178],"semantics":[152],"(FedHGS).":[153],"This":[154],"enhances":[156],"representation":[158],"preferences":[162],"improves":[164],"by":[170],"features":[175],"mining.":[180],"Additionally,":[181],"it":[182],"introduces":[183],"distillation":[186],"alignment":[187],"performance-aware":[189],"balance":[192],"across":[195],"improve":[198],"Finally,":[207],"extensive":[208],"experiments":[209],"are":[210],"conducted":[211],"verify":[213],"both":[214],"advantages":[220],"FedHGS.":[222]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}