{"id":"https://openalex.org/W2991030707","doi":"https://doi.org/10.1109/access.2019.2956342","title":"HIBoosting: A Recommender System Based on a Gradient Boosting Machine","display_name":"HIBoosting: A Recommender System Based on a Gradient Boosting Machine","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2991030707","doi":"https://doi.org/10.1109/access.2019.2956342","mag":"2991030707"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2956342","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2956342","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08915796.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08915796.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078517869","display_name":"Yabin Shao","orcid":"https://orcid.org/0000-0003-1001-7132"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yabin Shao","raw_affiliation_strings":["School of Science, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-1001-7132","affiliations":[{"raw_affiliation_string":"School of Science, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039660115","display_name":"Chuanlong Wang","orcid":"https://orcid.org/0000-0003-4477-2566"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanlong Wang","raw_affiliation_strings":["School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-4477-2566","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I10535382"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.411,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.91509723,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"7","issue":null,"first_page":"171013","last_page":"171022"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9975000023841858,"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/T11478","display_name":"Caching and Content Delivery","score":0.9830999970436096,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/computer-science","display_name":"Computer science","score":0.8874144554138184},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.8450237512588501},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.6810528635978699},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6061934232711792},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.5524314641952515},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.5222678780555725},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5072317123413086},{"id":"https://openalex.org/keywords/information-filtering-system","display_name":"Information filtering system","score":0.4234161376953125},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40729933977127075},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38904455304145813},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36924001574516296},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.2910078465938568},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.2306801974773407}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8874144554138184},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8450237512588501},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.6810528635978699},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6061934232711792},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.5524314641952515},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.5222678780555725},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5072317123413086},{"id":"https://openalex.org/C178674793","wikidata":"https://www.wikidata.org/wiki/Q6031077","display_name":"Information filtering system","level":2,"score":0.4234161376953125},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40729933977127075},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38904455304145813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36924001574516296},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.2910078465938568},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2306801974773407}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2956342","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2956342","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08915796.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1db2cafbea274982ab0f9f9c825b72d9","is_oa":true,"landing_page_url":"https://doaj.org/article/1db2cafbea274982ab0f9f9c825b72d9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 171013-171022 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2956342","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2956342","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08915796.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G1322390581","display_name":"\u6a21\u7cca\u6570\u5546\u7a7a\u95f4\u7684\u4ee3\u6570\u548c\u5206\u6790\u6027\u8d28\u53ca\u5176\u5728\u673a\u5668\u7ffb\u8bd1\u4e2d\u7684\u5e94\u7528\u7814\u7a76","funder_award_id":"11671001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3576345172","display_name":null,"funder_award_id":"61876201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5632875977","display_name":null,"funder_award_id":"61763044","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":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2991030707.pdf","grobid_xml":"https://content.openalex.org/works/W2991030707.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W103340358","https://openalex.org/W1967863517","https://openalex.org/W1975563293","https://openalex.org/W2004147962","https://openalex.org/W2013912476","https://openalex.org/W2030808931","https://openalex.org/W2042281163","https://openalex.org/W2047729491","https://openalex.org/W2054141820","https://openalex.org/W2075010670","https://openalex.org/W2135029798","https://openalex.org/W2149288670","https://openalex.org/W2154851992","https://openalex.org/W2295598076","https://openalex.org/W2295739661","https://openalex.org/W2566971417","https://openalex.org/W2571694389","https://openalex.org/W2592438485","https://openalex.org/W2599487467","https://openalex.org/W2616210849","https://openalex.org/W2743114144","https://openalex.org/W2743159750","https://openalex.org/W2768160734","https://openalex.org/W2781005404","https://openalex.org/W2783807530","https://openalex.org/W2784203924","https://openalex.org/W2884134047","https://openalex.org/W2889386526","https://openalex.org/W2897676029","https://openalex.org/W2942060499","https://openalex.org/W2945114750","https://openalex.org/W2962756421","https://openalex.org/W2963207245","https://openalex.org/W2963707260","https://openalex.org/W3104097132","https://openalex.org/W4244707235","https://openalex.org/W4251597219","https://openalex.org/W4252608527","https://openalex.org/W6680012447","https://openalex.org/W6741898958","https://openalex.org/W6747200787","https://openalex.org/W6751125968"],"related_works":["https://openalex.org/W2735929803","https://openalex.org/W4220714703","https://openalex.org/W3008845055","https://openalex.org/W4376854386","https://openalex.org/W2202724490","https://openalex.org/W2967733078","https://openalex.org/W2508671622","https://openalex.org/W2772628444","https://openalex.org/W1484355083","https://openalex.org/W2098758514"],"abstract_inverted_index":{"Based":[0],"on":[1,113,192],"explicit":[2],"data,":[3],"collaborative":[4],"filtering":[5],"is":[6],"one":[7],"of":[8,13,21,34,82,91,120,133,183,187,208],"the":[9,18,32,42,56,88,118,129,146,193,206],"most":[10],"valuable":[11],"technologies":[12],"a":[14,22,70,110,114,155,209],"recommender":[15,23,210],"system.":[16,211],"However,":[17],"further":[19],"development":[20],"system":[24],"has":[25,201],"been":[26],"restricted":[27],"to":[28,86,116,127,161],"some":[29,48],"extent":[30],"by":[31,45,137,154],"problems":[33],"cold":[35],"start":[36],"and":[37,62,97,142,195],"data":[38,46,51,99],"sparsity.":[39],"To":[40],"weaken":[41],"effect":[43],"caused":[44],"loss,":[47],"implicit":[49],"feedback":[50],"are":[52,125,149],"typically":[53],"introduced":[54],"into":[55],"recommendation":[57,166],"such":[58],"as":[59],"social":[60,93],"information":[61,72,90,102,174,176,189],"attribute":[63],"data.":[64],"In":[65],"this":[66],"paper,":[67],"we":[68,108],"propose":[69],"heterogeneous":[71,101,173,188],"boosting":[73,157],"model":[74,79,169],"for":[75,151],"recommendations":[76],"(HIBoosting).":[77],"The":[78,168],"takes":[80],"advantage":[81],"different":[83,105],"network":[84],"meta-paths":[85],"mine":[87],"potential":[89],"user":[92,140],"networks,":[94,177],"object":[95],"metadata":[96],"interactive":[98],"in":[100,175,205],"networks.":[103,190],"For":[104],"semantic":[106],"information,":[107],"use":[109,182],"random-walk":[111],"based":[112],"meta-path":[115],"calculate":[117],"similarities":[119],"users":[121,134,163],"or":[122,135],"items,":[123],"which":[124],"used":[126,150],"extract":[128],"low-dimensional":[130],"embedded":[131,147],"features":[132,148],"items":[136],"factorization,":[138],"construct":[139],"profiles":[141],"item":[143],"profiles.":[144],"Finally,":[145],"integrated":[152],"learning":[153],"gradient":[156],"decision":[158],"tree":[159],"(GBDT)":[160],"provide":[162],"with":[164],"better":[165],"services.":[167],"not":[170],"only":[171],"integrates":[172],"but":[178],"also":[179],"makes":[180],"full":[181],"mining":[184],"latent":[185],"relations":[186],"Experiments":[191],"CiaoDVD":[194],"Lastfm":[196],"datasets":[197],"show":[198],"that":[199],"HIBoosting":[200],"made":[202],"great":[203],"progress":[204],"accuracy":[207]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}