{"id":"https://openalex.org/W2605078958","doi":"https://doi.org/10.1145/3036290.3036313","title":"A Fast-training Approach Using ELM for Satisfaction Analysis of Call Centers","display_name":"A Fast-training Approach Using ELM for Satisfaction Analysis of Call Centers","publication_year":2017,"publication_date":"2017-01-13","ids":{"openalex":"https://openalex.org/W2605078958","doi":"https://doi.org/10.1145/3036290.3036313","mag":"2605078958"},"language":"en","primary_location":{"id":"doi:10.1145/3036290.3036313","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3036290.3036313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 International Conference on Machine Learning and Soft Computing","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/A5100375073","display_name":"Jing Liu","orcid":"https://orcid.org/0000-0002-9031-6433"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jing Liu","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology(BIT)"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology(BIT)","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100657997","display_name":"Yingnan Zhang","orcid":"https://orcid.org/0000-0002-5707-9413"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingnan Zhang","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology(BIT)"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology(BIT)","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081724582","display_name":"Jin Hu","orcid":"https://orcid.org/0000-0002-7563-4716"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Hu","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology(BIT)"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology(BIT)","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100642395","display_name":"Xiang Xie","orcid":"https://orcid.org/0000-0002-5135-0110"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Xie","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology(BIT)"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology(BIT)","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110518840","display_name":"Shilei Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shilei Huang","raw_affiliation_strings":["Shenzhen Research Institute of Beijing Institute of Technology (BIT)"],"affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Beijing Institute of Technology (BIT)","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100375073"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.195,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.59520333,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"143","last_page":"147"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9987999796867371,"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"}},"topics":[{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9987999796867371,"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/T13717","display_name":"Advanced Algorithms and Applications","score":0.9707000255584717,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.970300018787384,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6658638715744019},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.473088800907135},{"id":"https://openalex.org/keywords/customer-satisfaction","display_name":"Customer satisfaction","score":0.4430275857448578},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08135780692100525},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.06156989932060242}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6658638715744019},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.473088800907135},{"id":"https://openalex.org/C191511416","wikidata":"https://www.wikidata.org/wiki/Q999278","display_name":"Customer satisfaction","level":2,"score":0.4430275857448578},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08135780692100525},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.06156989932060242},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3036290.3036313","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3036290.3036313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 International Conference on Machine Learning and Soft Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4399999976158142}],"awards":[{"id":"https://openalex.org/G7316842256","display_name":null,"funder_award_id":"61473041,61571044,11590772","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2026131661","https://openalex.org/W2085662862","https://openalex.org/W2110996350","https://openalex.org/W2111072639","https://openalex.org/W2127773386","https://openalex.org/W2144005487","https://openalex.org/W2153635508","https://openalex.org/W2296199791","https://openalex.org/W2400139865","https://openalex.org/W2466953548","https://openalex.org/W2626699878","https://openalex.org/W2759454105"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W230091440","https://openalex.org/W2390279801","https://openalex.org/W2233261550","https://openalex.org/W2358668433","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2997094352"],"abstract_inverted_index":{"Analysis":[0],"of":[1,8,68,78,87,105,118],"the":[2,6,26,30,40,56,62,64,75,109,115,119,128],"customers'":[3,27,31],"satisfaction":[4,19,28],"guarantees":[5],"improvement":[7],"service":[9],"quality":[10],"in":[11,131],"call":[12,42],"centers.":[13],"In":[14],"this":[15],"paper,":[16],"an":[17],"intelligent":[18],"recognition":[20],"system":[21],"is":[22,70,80,124],"introduced":[23],"to":[24,61,73,82,92,100,127],"analyze":[25],"through":[29],"emotion":[32],"recognition.":[33],"The":[34,84],"nature":[35],"dialogues":[36],"are":[37,53],"collected":[38],"from":[39,90,98],"Chinese":[41],"center.":[43],"Support":[44],"Vector":[45],"Machine":[46,51],"(SVM)":[47],"and":[48],"Extreme":[49],"Learning":[50],"(ELM)":[52],"used":[54],"for":[55],"mapping":[57],"model":[58,129],"respectively.":[59],"According":[60],"experiment,":[63],"best":[65,76],"F":[66,77],"score":[67],"SVM":[69,88],"0.71.":[71],"Compared":[72],"SVM,":[74],"ELM":[79,107,123,135],"up":[81],"0.723.":[83],"training":[85,110,121],"time":[86,111],"ranges":[89,97],"1268s":[91],"5002s":[93],"while":[94],"ELM's":[95],"only":[96],"7.28s":[99],"15.82s,":[101],"with":[102],"a":[103,137],"decrease":[104],"99%.":[106],"shortens":[108],"largely":[112],"without":[113],"damaging":[114],"performance.":[116],"Because":[117],"faster":[120],"speed,":[122],"more":[125],"beneficial":[126],"updating":[130],"real":[132],"time.":[133],"Therefore,":[134],"has":[136],"great":[138],"edge":[139],"on":[140],"online":[141],"learning.":[142]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}