{"id":"https://openalex.org/W4306317646","doi":"https://doi.org/10.1145/3511808.3557609","title":"Heterogeneous Hypergraph Neural Network for Friend Recommendation with Human Mobility","display_name":"Heterogeneous Hypergraph Neural Network for Friend Recommendation with Human Mobility","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306317646","doi":"https://doi.org/10.1145/3511808.3557609"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557609","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557609","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100727698","display_name":"Yongkang Li","orcid":"https://orcid.org/0000-0001-6837-6184"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongkang Li","raw_affiliation_strings":["Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009062546","display_name":"Zipei Fan","orcid":"https://orcid.org/0000-0002-1442-1530"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zipei Fan","raw_affiliation_strings":["The University of Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086913695","display_name":"Jixiao Zhang","orcid":"https://orcid.org/0000-0002-8302-4731"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jixiao Zhang","raw_affiliation_strings":["Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047262978","display_name":"Dengheng Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dengheng Shi","raw_affiliation_strings":["Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112244458","display_name":"Tianqi Xu","orcid":"https://orcid.org/0000-0003-2359-5409"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianqi Xu","raw_affiliation_strings":["Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051629728","display_name":"Du Yin","orcid":"https://orcid.org/0000-0002-2345-0683"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Du Yin","raw_affiliation_strings":["Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000626453","display_name":"Jinliang Deng","orcid":"https://orcid.org/0000-0002-0759-947X"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jinliang Deng","raw_affiliation_strings":["University of Technology Sydney, Sydney, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046856721","display_name":"Xuan Song","orcid":"https://orcid.org/0000-0003-4042-7888"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Song","raw_affiliation_strings":["Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4209","last_page":"4213"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9990000128746033,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9871000051498413,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/hypergraph","display_name":"Hypergraph","score":0.9110562801361084},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7465991973876953},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5355121493339539},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5194405913352966},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4948555827140808},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4796481728553772},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.477855384349823},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4722915291786194},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.46692702174186707},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4374116063117981},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3950190842151642},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37965911626815796},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1356041133403778}],"concepts":[{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.9110562801361084},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7465991973876953},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5355121493339539},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5194405913352966},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4948555827140808},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4796481728553772},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.477855384349823},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4722915291786194},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.46692702174186707},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4374116063117981},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3950190842151642},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37965911626815796},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1356041133403778},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"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:10.1145/3511808.3557609","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557609","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4884160023","display_name":"Heterogeneous Graph Neural Network based Federated Mobile Crowdsensing","funder_award_id":"23K24829","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2110953678","https://openalex.org/W2154851992","https://openalex.org/W2747329762","https://openalex.org/W2892880750","https://openalex.org/W2897730209","https://openalex.org/W2913696439","https://openalex.org/W2962756421","https://openalex.org/W2965477817","https://openalex.org/W3018698383","https://openalex.org/W3032521456","https://openalex.org/W3104097132","https://openalex.org/W3190664711"],"related_works":["https://openalex.org/W4376608589","https://openalex.org/W3138003926","https://openalex.org/W4300037846","https://openalex.org/W1630514295","https://openalex.org/W1537073411","https://openalex.org/W2963081352","https://openalex.org/W2472555608","https://openalex.org/W4376608938","https://openalex.org/W4288275998","https://openalex.org/W1532260067"],"abstract_inverted_index":{"Friend":[0],"recommendation":[1,27,137],"from":[2,21],"human":[3,22],"mobility":[4,23],"is":[5,16],"a":[6,96,110],"vital":[7],"real-world":[8,150],"application":[9],"of":[10,39,71,83,160],"location-based":[11],"social":[12,44],"networks":[13,45],"(LBSN).":[14],"It":[15],"necessary":[17],"to":[18,24,101],"recognize":[19],"patterns":[20],"assist":[25],"friend":[26,136],"because":[28],"previous":[29,40],"works":[30,41],"have":[31],"shown":[32],"complex":[33,68,103],"relations":[34],"between":[35],"them.":[36],"However,":[37],"most":[38],"either":[42],"modelled":[43],"and":[46,90],"user":[47,88],"trajectories":[48,89],"separately,":[49],"or":[50],"only":[51],"used":[52],"classical":[53],"simple":[54],"graph-based":[55],"methods":[56,147],"with":[57,123],"an":[58,115],"edge":[59],"linking":[60],"two":[61],"nodes":[62,82],"that":[63,77],"cannot":[64],"fully":[65],"model":[66,87,142,162],"the":[67,75,134,145,158],"data":[69],"structure":[70],"LBSN.":[72],"Inspired":[73],"by":[74],"fact":[76],"hyperedges":[78,94],"can":[79,128],"connect":[80],"multiple":[81],"different":[84],"types,":[85],"we":[86,108],"check-in":[91],"records":[92],"as":[93],"in":[95],"novel":[97],"heterogeneous":[98,118],"LBSN":[99],"hypergraph":[100,119,130],"represent":[102],"spatio-temporal":[104],"information.":[105],"And":[106],"then,":[107],"design":[109],"type-specific":[111],"attention":[112],"mechanism":[113],"for":[114,133],"end-to-end":[116],"trainable":[117],"neural":[120],"network":[121],"(HHGNN)":[122],"supervised":[124],"contrastive":[125],"learning,":[126],"which":[127],"learn":[129],"node":[131],"embedding":[132],"next":[135],"task.":[138],"At":[139],"last,":[140],"our":[141],"HHGNN":[143],"outperforms":[144],"state-of-the-art":[146],"on":[148],"four":[149],"city":[151],"datasets,":[152],"while":[153],"ablation":[154],"studies":[155],"also":[156],"confirm":[157],"effectiveness":[159],"each":[161],"part.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":8}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
