{"id":"https://openalex.org/W2783190018","doi":"https://doi.org/10.1109/glocom.2017.8254481","title":"An Unbalanced Data Hybrid-Sampling Algorithm Based on Multi-Information Fusion","display_name":"An Unbalanced Data Hybrid-Sampling Algorithm Based on Multi-Information Fusion","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2783190018","doi":"https://doi.org/10.1109/glocom.2017.8254481","mag":"2783190018"},"language":"en","primary_location":{"id":"doi:10.1109/glocom.2017.8254481","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2017.8254481","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2017 - 2017 IEEE Global Communications Conference","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/A5100712817","display_name":"Sijia Chen","orcid":"https://orcid.org/0000-0001-6246-0940"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sijia Chen","raw_affiliation_strings":["State Key Laboratory of IntegratedServices Networks, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of IntegratedServices Networks, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035560190","display_name":"Bin Song","orcid":"https://orcid.org/0000-0002-8096-3370"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Song","raw_affiliation_strings":["State Key Laboratory of IntegratedServices Networks, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of IntegratedServices Networks, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100709310","display_name":"Jie Guo","orcid":"https://orcid.org/0000-0003-4975-0315"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Guo","raw_affiliation_strings":["State Key Laboratory of IntegratedServices Networks, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of IntegratedServices Networks, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060514022","display_name":"Xiaojiang Du","orcid":"https://orcid.org/0000-0003-4235-9671"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaojiang Du","raw_affiliation_strings":["Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100712817"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.195,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.64744987,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"39","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9994000196456909,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9994000196456909,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9672999978065491,"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/T13429","display_name":"Electricity Theft Detection Techniques","score":0.9559000134468079,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.7860780954360962},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7235931754112244},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6604846715927124},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6114354133605957},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5069153904914856},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5056354999542236},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4524983763694763},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.446024090051651},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32008010149002075},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29587048292160034},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17821693420410156}],"concepts":[{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.7860780954360962},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7235931754112244},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6604846715927124},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6114354133605957},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5069153904914856},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5056354999542236},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4524983763694763},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.446024090051651},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32008010149002075},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29587048292160034},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17821693420410156},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/glocom.2017.8254481","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2017.8254481","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2017 - 2017 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1964089535","https://openalex.org/W1966748751","https://openalex.org/W1984323748","https://openalex.org/W1986959058","https://openalex.org/W1993220166","https://openalex.org/W1996523702","https://openalex.org/W2006210519","https://openalex.org/W2022477494","https://openalex.org/W2025773596","https://openalex.org/W2049280902","https://openalex.org/W2087240369","https://openalex.org/W2094947835","https://openalex.org/W2096451472","https://openalex.org/W2097521902","https://openalex.org/W2098254218","https://openalex.org/W2104167780","https://openalex.org/W2104933073","https://openalex.org/W2114337635","https://openalex.org/W2124297996","https://openalex.org/W2128254529","https://openalex.org/W2132791018","https://openalex.org/W2139986471","https://openalex.org/W2140607818","https://openalex.org/W2148143831","https://openalex.org/W2162572433","https://openalex.org/W2164330572","https://openalex.org/W2172165257","https://openalex.org/W2338318698","https://openalex.org/W2343044157","https://openalex.org/W2345681014","https://openalex.org/W2360393060","https://openalex.org/W2562319768","https://openalex.org/W6635474240","https://openalex.org/W6675634716","https://openalex.org/W6682141768"],"related_works":["https://openalex.org/W4390608645","https://openalex.org/W4247566972","https://openalex.org/W4394895745","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W2910064364","https://openalex.org/W4200136508","https://openalex.org/W2042102171"],"abstract_inverted_index":{"The":[0,106],"emergence":[1],"of":[2,26,51,57,75,91,120,143,165,183],"big":[3,27],"data":[4,10,14,95,122],"bringsnewissues":[5],"and":[6,38,127,150,168,173,177],"challenges":[7],"for":[8,63],"the":[9,24,29,36,42,48,52,72,76,83,109,114,117,121,125,130,136,141,145,158,163,181],"imbalance":[11],"problem.Therefore,":[12],"unbalanced":[13,94],"sampling":[15,31,166],"technology":[16],"has":[17],"been":[18],"a":[19,54,68,170],"hot":[20],"research":[21],"topic":[22],"in":[23,41,67,71,103,180],"field":[25],"data.However,":[28],"existing":[30],"methods":[32],"cannot":[33],"accurately":[34],"define":[35,124],"harmful":[37],"useless":[39],"samplescontained":[40],"originaldataset.":[43],"That":[44],"is,":[45],"based":[46,98],"on":[47,99,152],"single":[49],"information":[50,111,119,137],"dataset,":[53],"large":[55],"number":[56],"actuallyharmful":[58],"samples":[59,131],"are":[60],"being":[61],"used":[62],"sampling,":[64],"which":[65],"results":[66],"sharp":[69],"decline":[70],"identifiable":[73],"performance":[74,164],"sampled":[77],"data.":[78,185],"In":[79],"order":[80],"to":[81,123,140],"overcome":[82],"problems":[84],"caused":[85],"by":[86,113,135],"only":[87],"using":[88],"one":[89],"kind":[90],"information,":[92],"an":[93],"hybrid-sampling":[96],"algorithm":[97,146],"multi-information":[100],"fusion(MIFS)is":[101],"presented":[102],"this":[104],"paper.":[105],"MIFS":[107,159],"combines":[108],"feature":[110],"learned":[112],"boostingmodel":[115],"with":[116],"position":[118],"sample,":[126],"then":[128],"divides":[129],"into":[132],"different":[133],"subsets":[134],"contained.":[138],"According":[139],"definition":[142],"samples,":[144],"performs":[147],"corresponding":[148],"under-sampling":[149],"over-sampling":[151],"these":[153],"subsets.":[154],"Experiments":[155],"show":[156],"that":[157],"method":[160],"can":[161],"improve":[162],"operations":[167],"produce":[169],"high":[171],"F-score":[172],"AUC":[174],"against":[175],"bothminority":[176],"majority":[178],"classes":[179],"classification":[182],"balanced":[184]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
