{"id":"https://openalex.org/W2738943795","doi":"https://doi.org/10.1109/iwcmc.2017.7986390","title":"QoE prediction on imbalanced IPTV data based on multi-layer neural network","display_name":"QoE prediction on imbalanced IPTV data based on multi-layer neural network","publication_year":2017,"publication_date":"2017-06-01","ids":{"openalex":"https://openalex.org/W2738943795","doi":"https://doi.org/10.1109/iwcmc.2017.7986390","mag":"2738943795"},"language":"en","primary_location":{"id":"doi:10.1109/iwcmc.2017.7986390","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc.2017.7986390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC)","raw_type":"proceedings-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/A5088583364","display_name":"Chaoping Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chaoping Lv","raw_affiliation_strings":["College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102706482","display_name":"Ruochen Huang","orcid":"https://orcid.org/0009-0006-5297-2970"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruochen Huang","raw_affiliation_strings":["College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015036096","display_name":"Wenqin Zhuang","orcid":"https://orcid.org/0000-0001-6071-7861"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqin Zhuang","raw_affiliation_strings":["College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040173124","display_name":"Xin Wei","orcid":"https://orcid.org/0000-0001-6183-2298"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xin Wei","raw_affiliation_strings":["Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042142440","display_name":"Qiuxia Bao","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiuxia Bao","raw_affiliation_strings":["College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5088583364"],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":null,"apc_paid":null,"fwci":0.2731,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.6333185,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"818","last_page":"823"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9918000102043152,"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/T12720","display_name":"Multimedia Communication and Technology","score":0.9872000217437744,"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/iptv","display_name":"IPTV","score":0.950387716293335},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8478870391845703},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7747686505317688},{"id":"https://openalex.org/keywords/quality-of-experience","display_name":"Quality of experience","score":0.6154277920722961},{"id":"https://openalex.org/keywords/quality-of-service","display_name":"Quality of service","score":0.5304842591285706},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5031511187553406},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.48135071992874146},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.475106805562973},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4504663348197937},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.4399047791957855},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.41925573348999023},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41296011209487915},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4120941162109375}],"concepts":[{"id":"https://openalex.org/C2776855496","wikidata":"https://www.wikidata.org/wiki/Q177518","display_name":"IPTV","level":2,"score":0.950387716293335},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8478870391845703},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7747686505317688},{"id":"https://openalex.org/C2779333187","wikidata":"https://www.wikidata.org/wiki/Q3132648","display_name":"Quality of experience","level":3,"score":0.6154277920722961},{"id":"https://openalex.org/C5119721","wikidata":"https://www.wikidata.org/wiki/Q220501","display_name":"Quality of service","level":2,"score":0.5304842591285706},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5031511187553406},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.48135071992874146},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.475106805562973},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4504663348197937},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.4399047791957855},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.41925573348999023},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41296011209487915},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4120941162109375},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iwcmc.2017.7986390","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc.2017.7986390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1575173104","https://openalex.org/W1713735053","https://openalex.org/W1916769834","https://openalex.org/W1973482401","https://openalex.org/W1978984614","https://openalex.org/W2011331177","https://openalex.org/W2025620802","https://openalex.org/W2034415518","https://openalex.org/W2050542575","https://openalex.org/W2081608404","https://openalex.org/W2095705004","https://openalex.org/W2101937247","https://openalex.org/W2116422221","https://openalex.org/W2156077514","https://openalex.org/W2169240112","https://openalex.org/W2325386712","https://openalex.org/W2351381307","https://openalex.org/W2362238774","https://openalex.org/W2472768134","https://openalex.org/W2511148373","https://openalex.org/W2569554180","https://openalex.org/W6637525845","https://openalex.org/W6674330103","https://openalex.org/W6725063865"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W2775175000","https://openalex.org/W2772289118","https://openalex.org/W4402156073","https://openalex.org/W2354113885","https://openalex.org/W2136238146","https://openalex.org/W2269355511","https://openalex.org/W2068552192","https://openalex.org/W2111755990"],"abstract_inverted_index":{"IPTV":[0,13,22,46],"is":[1],"a":[2,23],"new":[3],"multimedia":[4],"service":[5,28],"over":[6],"the":[7,15,27,35,38,45,50,59,69,81,85,89,111,115,121,133,139],"Internet.":[8],"The":[9],"rapid":[10],"development":[11],"of":[12,17,19,40,53,84,101,141],"makes":[14],"assessment":[16],"quality":[18],"experience":[20],"in":[21],"hot":[24],"topic":[25],"to":[26,73,80,110,124],"providers.":[29],"In":[30],"this":[31],"paper,":[32],"we":[33,57,87,106,119],"study":[34],"relationship":[36],"between":[37],"record":[39],"some":[41,63],"viewing":[42],"parameters":[43],"from":[44],"set-top":[47],"box":[48],"and":[49,61,66,126],"users'":[51],"Quality":[52],"Experience":[54],"(QoE).":[55],"Firstly,":[56],"analyze":[58],"data":[60],"choose":[62],"important":[64],"attributions":[65],"then":[67],"map":[68],"trouble":[70],"tickets":[71],"table":[72],"QoE":[74,142],"representing":[75],"acceptable":[76],"or":[77],"unacceptable.":[78],"According":[79],"imbalanced":[82],"feature":[83],"dataset,":[86],"proposed":[88,122,134],"multi-layer":[90],"neural":[91],"network":[92],"using":[93],"BP":[94],"algorithm":[95],"based":[96],"on":[97],"SGD":[98],"for":[99],"prediction":[100],"QoE.":[102],"To":[103],"avoid":[104],"overfitting,":[105],"apply":[107],"dropout":[108],"method":[109],"model":[112,123],"when":[113],"training":[114],"dataset.":[116],"At":[117],"last,":[118],"compare":[120],"SVM":[125],"Decision":[127],"Tree.":[128],"Experimental":[129],"results":[130],"show":[131],"that":[132],"methods":[135],"can":[136],"indeed":[137],"improve":[138],"accuracy":[140],"prediction.":[143]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}