{"id":"https://openalex.org/W2967206233","doi":"https://doi.org/10.18293/seke2019-156","title":"A Deep Learning Model Based on Sparse Matrix for Point-of-Interest Recommendation","display_name":"A Deep Learning Model Based on Sparse Matrix for Point-of-Interest Recommendation","publication_year":2019,"publication_date":"2019-07-10","ids":{"openalex":"https://openalex.org/W2967206233","doi":"https://doi.org/10.18293/seke2019-156","mag":"2967206233"},"language":"en","primary_location":{"id":"doi:10.18293/seke2019-156","is_oa":true,"landing_page_url":"http://doi.org/10.18293/seke2019-156","pdf_url":"https://doi.org/10.18293/seke2019-156","source":{"id":"https://openalex.org/S4220650826","display_name":"Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering","issn_l":"2325-9000","issn":["2325-9000","2325-9086"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"International Conferences on Software Engineering and Knowledge Engineering","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://doi.org/10.18293/seke2019-156","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","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 & Software Engineering Chongqing University Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Big Data & Software Engineering Chongqing University Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"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/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":"Haoran Tang","raw_affiliation_strings":["School of Big Data & Software Engineering Chongqing University Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Big Data & Software Engineering Chongqing University Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100413684","display_name":"Yinghua Li","orcid":"https://orcid.org/0000-0003-1390-0393"},"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":"Yinghua Li","raw_affiliation_strings":["School of Big Data & Software Engineering Chongqing University Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Big Data & Software Engineering Chongqing University Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051769186","display_name":"Xin He","orcid":"https://orcid.org/0000-0003-4506-2750"},"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":"Xin He","raw_affiliation_strings":["School of Big Data & Software Engineering Chongqing University Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Big Data & Software Engineering Chongqing University Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I158842170"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2019","issue":null,"first_page":"379","last_page":"384"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.891700029373169,"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":0.891700029373169,"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/T14280","display_name":"Big Data Technologies and Applications","score":0.8349999785423279,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.8327000141143799,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7005258202552795},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.6736623048782349},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5268216133117676},{"id":"https://openalex.org/keywords/point-of-interest","display_name":"Point of interest","score":0.5186840295791626},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5120368599891663},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4585210680961609},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4506072700023651},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38391217589378357},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14243093132972717}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7005258202552795},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.6736623048782349},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5268216133117676},{"id":"https://openalex.org/C150140777","wikidata":"https://www.wikidata.org/wiki/Q960648","display_name":"Point of interest","level":2,"score":0.5186840295791626},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5120368599891663},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4585210680961609},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4506072700023651},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38391217589378357},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14243093132972717},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18293/seke2019-156","is_oa":true,"landing_page_url":"http://doi.org/10.18293/seke2019-156","pdf_url":"https://doi.org/10.18293/seke2019-156","source":{"id":"https://openalex.org/S4220650826","display_name":"Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering","issn_l":"2325-9000","issn":["2325-9000","2325-9086"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"International Conferences on Software Engineering and Knowledge Engineering","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18293/seke2019-156","is_oa":true,"landing_page_url":"http://doi.org/10.18293/seke2019-156","pdf_url":"https://doi.org/10.18293/seke2019-156","source":{"id":"https://openalex.org/S4220650826","display_name":"Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering","issn_l":"2325-9000","issn":["2325-9000","2325-9086"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"International Conferences on Software Engineering and Knowledge Engineering","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4037764578","display_name":null,"funder_award_id":"61602070","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6003087894","display_name":null,"funder_award_id":"61502062","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7839444592","display_name":"\u79fb\u52a8\u73af\u5883\u4e0b\u57fa\u4e8e\u5f02\u6784\u7a7a\u95f4\u4fe1\u606f\u7f51\u7edc\u7684\u793e\u4f1a\u5316\u670d\u52a1\u63a8\u8350\u7814\u7a76","funder_award_id":"61672117","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2967206233.pdf","grobid_xml":"https://content.openalex.org/works/W2967206233.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1982397092","https://openalex.org/W1995103535","https://openalex.org/W2049626361","https://openalex.org/W2051234849","https://openalex.org/W2070868259","https://openalex.org/W2073013176","https://openalex.org/W2079335968","https://openalex.org/W2082215541","https://openalex.org/W2087692915","https://openalex.org/W2109242993","https://openalex.org/W2112631146","https://openalex.org/W2139809240","https://openalex.org/W6668440036","https://openalex.org/W6670928367","https://openalex.org/W6884869861","https://openalex.org/W6998754214"],"related_works":["https://openalex.org/W2890423584","https://openalex.org/W3013764321","https://openalex.org/W4387560237","https://openalex.org/W4285148873","https://openalex.org/W3080678454","https://openalex.org/W1970330626","https://openalex.org/W2081219400","https://openalex.org/W2384787007","https://openalex.org/W2557895864","https://openalex.org/W2039647443"],"abstract_inverted_index":{"Point-of-interest":[0],"(POI)":[1],"recommendation":[2,25,36,51,65,121],"that":[3,140],"consists":[4],"of":[5,24,31,45,58,75,131],"location-based":[6],"social":[7],"networks":[8],"(LBSNs)":[9],"and":[10,47,52,90,94],"provides":[11],"personal":[12],"services":[13],"for":[14,122,127],"users":[15,89],"has":[16,145],"become":[17],"an":[18],"important":[19],"part":[20],"in":[21],"the":[22,29,56,85,102,129,141],"field":[23],"system.":[26],"Due":[27],"to":[28,117],"sparseness":[30],"user":[32,76],"check-in":[33],"matrix,":[34],"POI":[35,64,120],"faces":[37],"great":[38],"challenges.":[39],"However,":[40],"most":[41],"researches":[42],"just":[43],"consider":[44],"spatial":[46],"temporal":[48],"impact":[49],"on":[50,72,135],"do":[53],"not":[54],"solve":[55],"problem":[57,130],"sparsity.":[59],"This":[60],"paper":[61],"proposes":[62],"a":[63,146],"model":[66,142],"called":[67],"RBMNMF":[68],"which":[69,124],"is":[70,92,125],"based":[71],"sparse":[73,104],"matrix":[74,105,109],"check-ins.":[77],"Firstly,":[78],"by":[79,106],"stacking":[80],"restricted":[81],"Boltzmann":[82],"machines":[83],"(RBM),":[84],"potential":[86],"relationship":[87],"between":[88],"POIs":[91],"learned":[93],"multiple":[95],"user-POI":[96],"matrices":[97,116],"are":[98],"extracted.":[99],"Second,":[100],"fill":[101],"original":[103],"using":[107],"non-negative":[108],"factorization":[110],"(NMF).":[111],"Finally,":[112],"fuse":[113],"those":[114],"prediction":[115],"generate":[118],"final":[119],"users,":[123],"benefit":[126],"solving":[128],"sparsity":[132],"effectively.":[133],"Experiments":[134],"real-world":[136],"data":[137],"set":[138],"prove":[139],"we":[143],"propose":[144],"better":[147],"accuracy":[148],"than":[149],"traditional":[150],"algorithms.":[151]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
