{"id":"https://openalex.org/W2997690421","doi":"https://doi.org/10.1109/access.2019.2962075","title":"A Review Semantics Based Model for Rating Prediction","display_name":"A Review Semantics Based Model for Rating Prediction","publication_year":2019,"publication_date":"2019-12-25","ids":{"openalex":"https://openalex.org/W2997690421","doi":"https://doi.org/10.1109/access.2019.2962075","mag":"2997690421"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2962075","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2962075","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08941029.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":"review","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08941029.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046694984","display_name":"Renhua Cao","orcid":"https://orcid.org/0000-0002-9907-3925"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renhua Cao","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-9907-3925","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052689516","display_name":"Xingming Zhang","orcid":"https://orcid.org/0000-0002-8139-0156"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingming Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-8139-0156","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101687639","display_name":"Haoxiang Wang","orcid":"https://orcid.org/0000-0003-4474-838X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoxiang Wang","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-4474-838X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.8213,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.92637965,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"4714","last_page":"4723"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9979000091552734,"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/T10609","display_name":"Digital Marketing and Social Media","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8333683013916016},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.750409722328186},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5915128588676453},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.590009331703186},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5679457187652588},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.468097448348999},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.45655009150505066},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.440441757440567},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42900484800338745},{"id":"https://openalex.org/keywords/semantic-matching","display_name":"Semantic matching","score":0.42541176080703735},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.39546290040016174},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3260643482208252},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.18899548053741455},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.1686675250530243}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8333683013916016},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.750409722328186},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5915128588676453},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.590009331703186},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5679457187652588},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.468097448348999},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.45655009150505066},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.440441757440567},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42900484800338745},{"id":"https://openalex.org/C2778493491","wikidata":"https://www.wikidata.org/wiki/Q7449072","display_name":"Semantic matching","level":3,"score":0.42541176080703735},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.39546290040016174},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3260643482208252},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.18899548053741455},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.1686675250530243},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2962075","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2962075","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08941029.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:a1569c295f2344d1b3737df80574489a","is_oa":false,"landing_page_url":"https://doaj.org/article/a1569c295f2344d1b3737df80574489a","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 4714-4723 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2962075","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2962075","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08941029.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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.8100000023841858}],"awards":[{"id":"https://openalex.org/G101451814","display_name":null,"funder_award_id":"2017B010111003","funder_id":"https://openalex.org/F4320326680","funder_display_name":"Guangdong Polytechnic of Science and Technology"},{"id":"https://openalex.org/G4528470491","display_name":null,"funder_award_id":"D2190680","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320326680","display_name":"Guangdong Polytechnic of Science and Technology","ror":"https://ror.org/01wq2p249"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2997690421.pdf","grobid_xml":"https://content.openalex.org/works/W2997690421.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W39762900","https://openalex.org/W1522301498","https://openalex.org/W1720514416","https://openalex.org/W1832693441","https://openalex.org/W1994176837","https://openalex.org/W2045882407","https://openalex.org/W2054141820","https://openalex.org/W2054553473","https://openalex.org/W2061873838","https://openalex.org/W2099866409","https://openalex.org/W2137245235","https://openalex.org/W2142972908","https://openalex.org/W2152184085","https://openalex.org/W2514530580","https://openalex.org/W2573167395","https://openalex.org/W2575006718","https://openalex.org/W2605350416","https://openalex.org/W2606749808","https://openalex.org/W2725606191","https://openalex.org/W2767724106","https://openalex.org/W2783565819","https://openalex.org/W2786995169","https://openalex.org/W2788376297","https://openalex.org/W2788893025","https://openalex.org/W2798972759","https://openalex.org/W2899626049","https://openalex.org/W2913351023","https://openalex.org/W2954834218","https://openalex.org/W2964015378","https://openalex.org/W3097991661","https://openalex.org/W3100591234","https://openalex.org/W3100921056","https://openalex.org/W4231510805","https://openalex.org/W6601633812","https://openalex.org/W6631190155","https://openalex.org/W6639619044","https://openalex.org/W6726873649","https://openalex.org/W6732188020","https://openalex.org/W7070499600"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W4391621807","https://openalex.org/W2965083567","https://openalex.org/W4235240664","https://openalex.org/W1838576100","https://openalex.org/W2095886385","https://openalex.org/W2889616422","https://openalex.org/W2089704382","https://openalex.org/W3196281958","https://openalex.org/W1595649729"],"abstract_inverted_index":{"A":[0],"review":[1,54,78,98,102,111,127,157,174],"expresses":[2],"the":[3,17,33,51,66,86,89,97,101,106,110,121,130,143,156,160,163,169,173,178,180,187,192,204],"concerned":[4,149],"aspects":[5],"and":[6,20,27,59,68,105,138,219],"corresponding":[7],"assessments":[8],"a":[9,13,37,41,46,76,115,125,134,197],"customer":[10],"has":[11],"towards":[12],"particular":[14,126],"item.":[15],"Extracting":[16],"user's":[18],"interests":[19],"product's":[21],"features":[22,123,183],"from":[23],"their":[24],"aggregated":[25,52],"reviews":[26],"matching":[28],"them":[29],"together":[30],"to":[31,84,119,141,154,190],"predict":[32,191],"overall":[34,193],"rating":[35,107,188],"is":[36,82,166],"common":[38],"paradigm":[39,47],"in":[40,215],"review-based":[42,90],"recommender.":[43,91],"However,":[44],"such":[45],"trains":[48],"model":[49,206],"on":[50,196],"historical":[53],"which":[55,146],"grows":[56],"with":[57,168],"time":[58],"may":[60,70],"have":[61],"much":[62],"conflicting":[63],"semantics,":[64],"thus":[65],"scalability":[67],"accuracy":[69,218],"be":[71],"compromised.":[72],"In":[73,159,177],"this":[74],"paper,":[75],"novel":[77],"semantics":[79,99,103,112,131,165,170,175],"based":[80],"model(RSBM)":[81],"proposed":[83,205],"enhance":[85],"performance":[87],"of":[88,94,124,151,199,217],"It":[92],"consists":[93],"three":[95],"parts:":[96],"extractor,":[100],"generator":[104,132],"regressor.":[108],"Firstly,":[109],"extractor":[113],"uses":[114,133],"convolutional":[116],"neural":[117],"network(CNN)":[118],"extract":[120],"semantic":[122,182],"text.":[128],"Secondly,":[129],"memory-network":[135],"liked":[136],"structure":[137],"attention":[139],"mechanism":[140],"simulate":[142],"decision-making":[144],"process":[145],"assesses":[147],"each":[148],"aspect":[150],"an":[152],"item":[153],"generate":[155],"semantics.":[158],"training":[161],"phase,":[162],"generated":[164,181],"compared":[167],"extracted":[171],"by":[172],"extractor.":[176],"last,":[179],"are":[184],"fed":[185],"into":[186],"regressor":[189],"rating.":[194],"Experiments":[195],"series":[198],"reality":[200],"datasets":[201],"show":[202],"that":[203],"gains":[207],"better":[208],"performances":[209],"than":[210],"several":[211],"state-of-the-art":[212],"recommendation":[213],"approaches":[214],"terms":[216],"scalability.":[220]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
