{"id":"https://openalex.org/W3022522270","doi":"https://doi.org/10.1109/tcss.2020.2987846","title":"Deep Correlation Mining Based on Hierarchical Hybrid Networks for Heterogeneous Big Data Recommendations","display_name":"Deep Correlation Mining Based on Hierarchical Hybrid Networks for Heterogeneous Big Data Recommendations","publication_year":2020,"publication_date":"2020-05-08","ids":{"openalex":"https://openalex.org/W3022522270","doi":"https://doi.org/10.1109/tcss.2020.2987846","mag":"3022522270"},"language":"en","primary_location":{"id":"doi:10.1109/tcss.2020.2987846","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2020.2987846","pdf_url":null,"source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"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 Computational Social 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/A5055675863","display_name":"Xiaokang Zhou","orcid":"https://orcid.org/0000-0003-3488-4679"},"institutions":[{"id":"https://openalex.org/I171494771","display_name":"Shiga University","ror":"https://ror.org/01vvhy971","country_code":"JP","type":"education","lineage":["https://openalex.org/I171494771"]},{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xiaokang Zhou","raw_affiliation_strings":["Faculty of Data Science, Shiga University, Hikone, Japan","RIKEN Center for Advanced Intelligence Project, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0003-3488-4679","affiliations":[{"raw_affiliation_string":"Faculty of Data Science, Shiga University, Hikone, Japan","institution_ids":["https://openalex.org/I171494771"]},{"raw_affiliation_string":"RIKEN Center for Advanced Intelligence Project, Tokyo, Japan","institution_ids":["https://openalex.org/I4210126580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073441538","display_name":"Wei Liang","orcid":"https://orcid.org/0000-0002-0689-256X"},"institutions":[{"id":"https://openalex.org/I49934816","display_name":"Hunan University of Technology","ror":"https://ror.org/04j3vr751","country_code":"CN","type":"education","lineage":["https://openalex.org/I49934816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liang","raw_affiliation_strings":["Key Laboratory of Hunan Province for New Retail Virtual Reality Technology, Hunan University of Technology and Business, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-0689-256X","affiliations":[{"raw_affiliation_string":"Key Laboratory of Hunan Province for New Retail Virtual Reality Technology, Hunan University of Technology and Business, Changsha, China","institution_ids":["https://openalex.org/I49934816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091532881","display_name":"Kevin I\u2010Kai Wang","orcid":"https://orcid.org/0000-0001-8450-2558"},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Kevin I-Kai Wang","raw_affiliation_strings":["The University of Auckland, Auckland, New Zealand"],"raw_orcid":"https://orcid.org/0000-0001-8450-2558","affiliations":[{"raw_affiliation_string":"The University of Auckland, Auckland, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049154222","display_name":"Laurence T. Yang","orcid":"https://orcid.org/0000-0002-7986-4244"},"institutions":[{"id":"https://openalex.org/I197191942","display_name":"St. Francis Xavier University","ror":"https://ror.org/01wcaxs37","country_code":"CA","type":"education","lineage":["https://openalex.org/I197191942"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Laurence T. Yang","raw_affiliation_strings":["St. Francis Xavier University, Antigonish, Canada"],"raw_orcid":"https://orcid.org/0000-0002-7986-4244","affiliations":[{"raw_affiliation_string":"St. Francis Xavier University, Antigonish, Canada","institution_ids":["https://openalex.org/I197191942"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":51.1907,"has_fulltext":false,"cited_by_count":283,"citation_normalized_percentile":{"value":0.99855536,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"8","issue":"1","first_page":"171","last_page":"178"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9962000250816345,"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":0.9962000250816345,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9923999905586243,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9692000150680542,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7423465251922607},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6830431818962097},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5856027603149414},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5457884073257446},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4974100887775421},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47586482763290405},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4757768213748932},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4713786542415619},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4446578025817871},{"id":"https://openalex.org/keywords/router","display_name":"Router","score":0.4430786371231079},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4425141513347626}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7423465251922607},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6830431818962097},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5856027603149414},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5457884073257446},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4974100887775421},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47586482763290405},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4757768213748932},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4713786542415619},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4446578025817871},{"id":"https://openalex.org/C2775896111","wikidata":"https://www.wikidata.org/wiki/Q642560","display_name":"Router","level":2,"score":0.4430786371231079},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4425141513347626},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcss.2020.2987846","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2020.2987846","pdf_url":null,"source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"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 Computational Social Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5699999928474426}],"awards":[{"id":"https://openalex.org/G1489494493","display_name":null,"funder_award_id":"2019JJ40150","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"}],"funders":[{"id":"https://openalex.org/F4320322843","display_name":"Natural Science Foundation of\u00a0Hunan Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2009442627","https://openalex.org/W2041987923","https://openalex.org/W2513133360","https://openalex.org/W2519400179","https://openalex.org/W2559325834","https://openalex.org/W2595454738","https://openalex.org/W2600145262","https://openalex.org/W2610514569","https://openalex.org/W2625968153","https://openalex.org/W2731090626","https://openalex.org/W2753240733","https://openalex.org/W2757727956","https://openalex.org/W2778717889","https://openalex.org/W2790068678","https://openalex.org/W2791512297","https://openalex.org/W2794024860","https://openalex.org/W2807884258","https://openalex.org/W2809922372","https://openalex.org/W2884319684","https://openalex.org/W2897819140","https://openalex.org/W2898731665","https://openalex.org/W2940996842","https://openalex.org/W2941742282","https://openalex.org/W2960269662","https://openalex.org/W2964353755","https://openalex.org/W2965393225","https://openalex.org/W2973099934","https://openalex.org/W2975109141","https://openalex.org/W2994886533","https://openalex.org/W2995191368","https://openalex.org/W6753659652"],"related_works":["https://openalex.org/W2122026593","https://openalex.org/W4390608645","https://openalex.org/W4394895745","https://openalex.org/W4247566972","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W2910064364","https://openalex.org/W4200136508"],"abstract_inverted_index":{"The":[0],"advancement":[1],"of":[2,37,74,170],"several":[3],"significant":[4],"technologies,":[5],"such":[6],"as":[7],"artificial":[8],"intelligence,":[9,11],"cyber":[10],"and":[12,25,71,146,162,168,173],"machine":[13],"learning,":[14],"has":[15],"made":[16],"big":[17,53,155],"data":[18,54,156,164],"penetrate":[19],"not":[20],"only":[21],"into":[22],"the":[23,80,111,118,125,130,166],"industry":[24],"academic":[26],"field":[27],"but":[28],"also":[29],"our":[30,171],"daily":[31],"life":[32],"along":[33],"with":[34,117,124,136],"a":[35,46,72],"variety":[36],"cyber-enabled":[38],"applications.":[39],"In":[40],"this":[41],"article,":[42],"we":[43],"focus":[44],"on":[45,97,129,160],"deep":[47,98],"correlation":[48],"mining":[49],"method":[50],"in":[51,153],"heterogeneous":[52],"environments.":[55,157],"A":[56],"hierarchical":[57,131],"hybrid":[58],"network":[59,134],"(HHN)":[60],"model":[61,172],"is":[62,102,121,143],"constructed":[63],"to":[64,78,104,108,148],"describe":[65],"multitype":[66],"relationships":[67],"among":[68],"different":[69,91],"entities,":[70],"series":[73],"measures":[75],"are":[76],"defined":[77],"quantify":[79],"internal":[81],"correlations":[82,89],"within":[83],"one":[84],"specific":[85],"layer":[86],"or":[87],"external":[88],"between":[90],"layers.":[92],"An":[93,113,139],"intelligent":[94,126,140],"router":[95],"based":[96,128,159],"reinforcement":[99],"learning":[100],"framework":[101],"designed":[103,145],"generate":[105],"optimal":[106],"actions":[107],"route":[109],"across":[110,133],"HHN.":[112],"improved":[114],"random":[115],"walk":[116],"restart-based":[119],"algorithm":[120],"then":[122],"developed":[123],"router,":[127],"influence":[132],"associated":[135],"multiple":[137],"correlations.":[138],"recommendation":[141],"mechanism":[142],"finally":[144],"applied":[147],"support":[149],"users'":[150],"collaboration":[151],"works":[152],"scholarly":[154],"Experiments":[158],"DBLP":[161],"ResearchGate":[163],"show":[165],"practicability":[167],"usefulness":[169],"method.":[174]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":33},{"year":2024,"cited_by_count":66},{"year":2023,"cited_by_count":84},{"year":2022,"cited_by_count":59},{"year":2021,"cited_by_count":31},{"year":2020,"cited_by_count":9}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
