{"id":"https://openalex.org/W2528516053","doi":"https://doi.org/10.5430/air.v6n1p52","title":"Comparison of three data mining algorithms for potential 4G customers prediction","display_name":"Comparison of three data mining algorithms for potential 4G customers prediction","publication_year":2016,"publication_date":"2016-10-07","ids":{"openalex":"https://openalex.org/W2528516053","doi":"https://doi.org/10.5430/air.v6n1p52","mag":"2528516053"},"language":"en","primary_location":{"id":"doi:10.5430/air.v6n1p52","is_oa":true,"landing_page_url":"https://doi.org/10.5430/air.v6n1p52","pdf_url":"http://www.sciedu.ca/journal/index.php/air/article/download/9991/6293","source":{"id":"https://openalex.org/S4210167461","display_name":"Artificial Intelligence Research","issn_l":"1927-6974","issn":["1927-6974","1927-6982"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320842","host_organization_name":"Sciedu Press","host_organization_lineage":["https://openalex.org/P4310320842"],"host_organization_lineage_names":["Sciedu Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence Research","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"http://www.sciedu.ca/journal/index.php/air/article/download/9991/6293","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088967238","display_name":"Chun Gui","orcid":"https://orcid.org/0000-0002-4484-3339"},"institutions":[{"id":"https://openalex.org/I124644866","display_name":"Northwest Minzu University","ror":"https://ror.org/04cyy9943","country_code":"CN","type":"education","lineage":["https://openalex.org/I124644866"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun Gui","raw_affiliation_strings":["College of mathematics and computer science, Northwest University for Nationalities"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of mathematics and computer science, Northwest University for Nationalities","institution_ids":["https://openalex.org/I124644866"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008964526","display_name":"Qiang Lin","orcid":"https://orcid.org/0000-0002-0648-5665"},"institutions":[{"id":"https://openalex.org/I124644866","display_name":"Northwest Minzu University","ror":"https://ror.org/04cyy9943","country_code":"CN","type":"education","lineage":["https://openalex.org/I124644866"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Lin","raw_affiliation_strings":["College of mathematics and computer science, Northwest University for Nationalities"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of mathematics and computer science, Northwest University for Nationalities","institution_ids":["https://openalex.org/I124644866"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I124644866"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.15201644,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"6","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7504120469093323},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6522970199584961},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.5525031685829163},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.510111391544342},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.506339430809021},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49578961730003357},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.4396980106830597},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.42249417304992676},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3738764822483063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3334782123565674},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.1032402515411377}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7504120469093323},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6522970199584961},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.5525031685829163},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.510111391544342},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.506339430809021},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49578961730003357},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.4396980106830597},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.42249417304992676},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3738764822483063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3334782123565674},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.1032402515411377},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5430/air.v6n1p52","is_oa":true,"landing_page_url":"https://doi.org/10.5430/air.v6n1p52","pdf_url":"http://www.sciedu.ca/journal/index.php/air/article/download/9991/6293","source":{"id":"https://openalex.org/S4210167461","display_name":"Artificial Intelligence Research","issn_l":"1927-6974","issn":["1927-6974","1927-6982"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320842","host_organization_name":"Sciedu Press","host_organization_lineage":["https://openalex.org/P4310320842"],"host_organization_lineage_names":["Sciedu Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence Research","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.5430/air.v6n1p52","is_oa":true,"landing_page_url":"https://doi.org/10.5430/air.v6n1p52","pdf_url":"http://www.sciedu.ca/journal/index.php/air/article/download/9991/6293","source":{"id":"https://openalex.org/S4210167461","display_name":"Artificial Intelligence Research","issn_l":"1927-6974","issn":["1927-6974","1927-6982"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320842","host_organization_name":"Sciedu Press","host_organization_lineage":["https://openalex.org/P4310320842"],"host_organization_lineage_names":["Sciedu Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence Research","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5600000023841858,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G2811595801","display_name":null,"funder_award_id":"31920140058","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G7119918162","display_name":"\u57fa\u4e8e\u5065\u5eb7\u6d41\u6570\u636e\u7684\u5065\u5eb7\u6f14\u8fdb\u8d8b\u52bf\u8bc6\u522b\u4e0e\u5b9e\u65f6\u72b6\u6001\u8bc4\u6d4b\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61562075","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"},{"id":"https://openalex.org/F4320322880","display_name":"Natural Science Foundation of Gansu Province","ror":null},{"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/W2528516053.pdf","grobid_xml":"https://content.openalex.org/works/W2528516053.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W1552339598","https://openalex.org/W1556344493","https://openalex.org/W1740337471","https://openalex.org/W2082152047","https://openalex.org/W2112076978","https://openalex.org/W2144182447","https://openalex.org/W2911964244","https://openalex.org/W3204438512","https://openalex.org/W4247829154","https://openalex.org/W4252441533","https://openalex.org/W4254420769","https://openalex.org/W4402951240","https://openalex.org/W6665888333"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2357409937","https://openalex.org/W2978674666","https://openalex.org/W2074430941","https://openalex.org/W2113096305","https://openalex.org/W2358294942","https://openalex.org/W4317422759","https://openalex.org/W4367460280","https://openalex.org/W4328049145"],"abstract_inverted_index":{"The":[0,98],"size":[1],"and":[2,22,85,94,106,110],"number":[3],"of":[4,12,75,103,115],"telecom":[5,34,46],"databases":[6],"are":[7,31,108],"growing":[8],"quickly":[9],"but":[10],"most":[11],"the":[13,68,73,113,123],"data":[14,28,50,76],"has":[15],"not":[16],"been":[17],"analyzed":[18],"for":[19,33],"revealing":[20],"thehidden":[21],"valuable":[23],"intellectual.":[24],"Models":[25],"developed":[26],"from":[27,44],"mining":[29,51,77],"techniques":[30,78],"useful":[32],"to":[35,66,79],"make":[36],"right":[37],"prediction.The":[38],"dataset":[39,90],"contains":[40],"one":[41],"million":[42],"customers":[43],"a":[45],"company.":[47],"We":[48],"implement":[49],"techniques,":[52],"i.e.":[53],",":[54],"AdaboostM1(ABM)":[55],"algorithm,":[56,60],"Na\u00efve":[57],"Bayes":[58],"(NB)":[59],"Local":[61],"Outlier":[62],"Factor":[63],"(LOF)":[64],"algorithm":[65,120],"develop":[67,80],"predictive":[69,83],"models.":[70],"Thispaper":[71],"studies":[72],"application":[74],"4G":[81],"customer":[82],"models":[84,88],"compares":[86],"three":[87],"onour":[89],"through":[91],"precision,":[92],"recall,":[93],"cumulative":[95,116],"recall":[96,117],"curve.":[97],"result":[99],"is":[100,122],"that":[101],"precision":[102],"ABM,":[104],"NB":[105,119],"LOF":[107],"0.6016,0.6735":[109],"0.3844.":[111],"From":[112],"aspects":[114],"curve":[118],"also":[121],"best":[124],"one.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
