{"id":"https://openalex.org/W4386902921","doi":"https://doi.org/10.1109/tsc.2023.3317642","title":"Robust QoS Prediction Based on Reputation Integrated Graph Convolution Network","display_name":"Robust QoS Prediction Based on Reputation Integrated Graph Convolution Network","publication_year":2023,"publication_date":"2023-09-20","ids":{"openalex":"https://openalex.org/W4386902921","doi":"https://doi.org/10.1109/tsc.2023.3317642"},"language":"en","primary_location":{"id":"doi:10.1109/tsc.2023.3317642","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsc.2023.3317642","pdf_url":null,"source":{"id":"https://openalex.org/S204223317","display_name":"IEEE Transactions on Services Computing","issn_l":"1939-1374","issn":["1939-1374","2372-0204"],"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 Services Computing","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/A5041235438","display_name":"Ziteng Wu","orcid":"https://orcid.org/0009-0000-4428-3557"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziteng Wu","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","School of Computer and Information Technology, Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0000-4428-3557","affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100352102","display_name":"Ding Ding","orcid":"https://orcid.org/0000-0002-4108-3418"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ding Ding","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","School of Computer and Information Technology, Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4108-3418","affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088447454","display_name":"Yuting Xiu","orcid":"https://orcid.org/0009-0005-1859-8674"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuting Xiu","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","School of Computer and Information Technology, Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0005-1859-8674","affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102898708","display_name":"Yuekun Zhao","orcid":"https://orcid.org/0009-0004-1618-7532"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuekun Zhao","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","School of Computer and Information Technology, Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0004-1618-7532","affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101051094","display_name":"Jing Hong","orcid":"https://orcid.org/0009-0005-2348-0347"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Hong","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","School of Computer and Information Technology, Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0005-2348-0347","affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":7.691,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.97337671,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"17","issue":"3","first_page":"1154","last_page":"1167"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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/T11478","display_name":"Caching and Content Delivery","score":0.9977999925613403,"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"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9805999994277954,"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":0.8665936589241028},{"id":"https://openalex.org/keywords/quality-of-service","display_name":"Quality of service","score":0.6766486763954163},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6206249594688416},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6199753880500793},{"id":"https://openalex.org/keywords/reputation","display_name":"Reputation","score":0.5895511507987976},{"id":"https://openalex.org/keywords/web-service","display_name":"Web service","score":0.5532210469245911},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5447677969932556},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49941349029541016},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.47535866498947144},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4152095913887024},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3012450039386749},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.29408350586891174},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.1965155005455017},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.169295072555542}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8665936589241028},{"id":"https://openalex.org/C5119721","wikidata":"https://www.wikidata.org/wiki/Q220501","display_name":"Quality of service","level":2,"score":0.6766486763954163},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6206249594688416},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6199753880500793},{"id":"https://openalex.org/C48798503","wikidata":"https://www.wikidata.org/wiki/Q877546","display_name":"Reputation","level":2,"score":0.5895511507987976},{"id":"https://openalex.org/C35578498","wikidata":"https://www.wikidata.org/wiki/Q193424","display_name":"Web service","level":2,"score":0.5532210469245911},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5447677969932556},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49941349029541016},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.47535866498947144},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4152095913887024},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3012450039386749},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.29408350586891174},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.1965155005455017},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.169295072555542},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsc.2023.3317642","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsc.2023.3317642","pdf_url":null,"source":{"id":"https://openalex.org/S204223317","display_name":"IEEE Transactions on Services Computing","issn_l":"1939-1374","issn":["1939-1374","2372-0204"],"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 Services Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1146114478","display_name":null,"funder_award_id":"2022JBZY023","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1529703297","https://openalex.org/W1558424403","https://openalex.org/W2030239032","https://openalex.org/W2060017308","https://openalex.org/W2091381870","https://openalex.org/W2140597141","https://openalex.org/W2182261282","https://openalex.org/W2295458067","https://openalex.org/W2323283582","https://openalex.org/W2407292501","https://openalex.org/W2537653515","https://openalex.org/W2575006718","https://openalex.org/W2611027303","https://openalex.org/W2738639449","https://openalex.org/W2755258594","https://openalex.org/W2788376297","https://openalex.org/W2799431042","https://openalex.org/W2884048157","https://openalex.org/W2930749509","https://openalex.org/W2945827670","https://openalex.org/W2949655105","https://openalex.org/W3045200674","https://openalex.org/W3083741327","https://openalex.org/W3093002391","https://openalex.org/W3100278010","https://openalex.org/W3120815295","https://openalex.org/W3129785657","https://openalex.org/W3132700449","https://openalex.org/W3156564332","https://openalex.org/W3204880307","https://openalex.org/W3210910782","https://openalex.org/W4205365155","https://openalex.org/W4224312753","https://openalex.org/W4284688665","https://openalex.org/W4312750789","https://openalex.org/W4316126716","https://openalex.org/W4380986298","https://openalex.org/W6680451568"],"related_works":["https://openalex.org/W4392337488","https://openalex.org/W2102271161","https://openalex.org/W4313425421","https://openalex.org/W4388714791","https://openalex.org/W2361883455","https://openalex.org/W2952832228","https://openalex.org/W2909324362","https://openalex.org/W2372868951","https://openalex.org/W570712888","https://openalex.org/W4400047197"],"abstract_inverted_index":{"With":[0],"the":[1,15,50,53,59,65,68,124,134,138,165,189,223,238],"proliferation":[2],"of":[3,28,30,52,55,67,127,137,146,164,215,226,240],"Web":[4,60],"services,":[5],"it":[6,230],"is":[7,47,86,120,178,231],"very":[8,232],"difficult":[9],"for":[10],"inexperienced":[11],"users":[12,128,147],"to":[13,91,122,160,181,193],"select":[14],"most":[16],"appropriate":[17],"service":[18,38,61,169],"among":[19],"numerous":[20],"functionally":[21],"identical":[22],"or":[23],"similar":[24],"candidates,":[25],"thus":[26],"prediction":[27,70,242],"Quality":[29],"Service":[31],"(QoS)":[32],"becomes":[33],"a":[34,44,79,174],"growing":[35],"concern":[36],"in":[37,49,88,168,188,236],"discovery,":[39],"selection":[40],"and":[41,94,108,115,133,148,185,209,212,234,245],"recommendation.":[42],"However,":[43],"huge":[45],"challenge":[46],"that":[48,201],"reality":[51],"existence":[54],"untrustworthy":[56,227],"users,":[57],"how":[58],"recommendation":[62],"system":[63],"keeps":[64],"robustness":[66],"QoS":[69,96,110,140,196,241],"while":[71],"maintaining":[72],"high":[73],"accuracy.":[74],"To":[75],"address":[76],"this":[77,89,172],"problem,":[78],"Reputation":[80,103],"Integrated":[81],"Graph":[82],"Convolution":[83],"Network":[84],"(RIGCN)":[85],"developed":[87],"paper":[90],"realize":[92],"robust":[93,233],"accurate":[95],"prediction.":[97,197],"RIGCN":[98,203],"has":[99],"three":[100],"main":[101],"parts:":[102],"Extraction,":[104],"Multi-source":[105],"Feature":[106],"Extraction":[107],"GCN-based":[109],"Prediction.":[111],"First,":[112],"an":[113,157],"Outlier":[114],"Pattern":[116],"Measure":[117],"(OPM)":[118],"method":[119],"proposed":[121],"extract":[123,208],"real":[125],"reputation":[126,187],"based":[129],"on":[130],"both":[131],"outliers":[132],"distribution":[135],"patterns":[136],"historical":[139],"interaction":[141],"records.":[142],"Second,":[143],"deep":[144],"features":[145,184,214],"services":[149],"are":[150],"captured":[151],"by":[152],"multi-source":[153,183,217],"feature":[154],"extraction":[155],"with":[156,243],"attention":[158],"mechanism":[159],"make":[161],"full":[162],"use":[163],"contextual":[166],"information":[167],"invocation.":[170],"On":[171],"basis,":[173],"graph":[175],"convolution":[176],"network":[177],"specially":[179],"designed":[180],"integrate":[182],"user":[186],"message":[190],"propagation":[191],"process":[192],"complete":[194],"final":[195],"Experimental":[198],"results":[199],"demonstrate":[200],"our":[202],"approach":[204],"can":[205,221],"not":[206],"only":[207],"utilize":[210],"implicit":[211],"explicit":[213],"various":[216],"data,":[218],"but":[219],"also":[220],"reduce":[222],"negative":[224],"influence":[225],"users.":[228],"Therefore,":[229],"effective":[235],"improving":[237],"accuracy":[239],"sparse":[244],"noisy":[246],"data.":[247]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
