{"id":"https://openalex.org/W2587606547","doi":"https://doi.org/10.1109/smc.2016.7844752","title":"An instance selection framework for mining data streams to predict antibody-feature function relationships on RV144 HIV vaccine recipients","display_name":"An instance selection framework for mining data streams to predict antibody-feature function relationships on RV144 HIV vaccine recipients","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2587606547","doi":"https://doi.org/10.1109/smc.2016.7844752","mag":"2587606547"},"language":"en","primary_location":{"id":"doi:10.1109/smc.2016.7844752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2016.7844752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5023779408","display_name":"Ferdi Sarac","orcid":"https://orcid.org/0000-0002-7080-1634"},"institutions":[{"id":"https://openalex.org/I32394136","display_name":"Northumbria University","ror":"https://ror.org/049e6bc10","country_code":"GB","type":"education","lineage":["https://openalex.org/I32394136"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ferdi Sarac","raw_affiliation_strings":["Faculty of Engineering and Environment, University of Northumbria, Newcastle, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Environment, University of Northumbria, Newcastle, United Kingdom","institution_ids":["https://openalex.org/I32394136"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057405456","display_name":"H\u00fcseyin \u015eeker","orcid":"https://orcid.org/0000-0002-1255-9552"},"institutions":[{"id":"https://openalex.org/I32394136","display_name":"Northumbria University","ror":"https://ror.org/049e6bc10","country_code":"GB","type":"education","lineage":["https://openalex.org/I32394136"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Huseyin Seker","raw_affiliation_strings":["Faculty of Engineering and Environment, University of Northumbria, Newcastle, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Environment, University of Northumbria, Newcastle, United Kingdom","institution_ids":["https://openalex.org/I32394136"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8833,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.8563743,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"5","issue":null,"first_page":"003356","last_page":"003361"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9937999844551086,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9937999844551086,"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/T12391","display_name":"Artificial Immune Systems Applications","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T12535","display_name":"Machine Learning and Data Classification","score":0.9542999863624573,"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":0.6946025490760803},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6305176019668579},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.5361037254333496},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5185092687606812},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.46682897210121155},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4227871298789978},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42113563418388367},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32305967807769775},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25479841232299805}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6946025490760803},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6305176019668579},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.5361037254333496},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5185092687606812},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.46682897210121155},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4227871298789978},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42113563418388367},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32305967807769775},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25479841232299805},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/smc.2016.7844752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2016.7844752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},{"id":"pmh:oai:nrl.northumbria.ac.uk:30417","is_oa":false,"landing_page_url":"http://nrl.northumbria.ac.uk/30417/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401884","display_name":"Northumbria Research Link (Northumbria University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32394136","host_organization_name":"Northumbria University","host_organization_lineage":["https://openalex.org/I32394136"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Book Section"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.6700000166893005,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1505753439","https://openalex.org/W1968160919","https://openalex.org/W2011762057","https://openalex.org/W2026324356","https://openalex.org/W2052200679","https://openalex.org/W2081308844","https://openalex.org/W2102148524","https://openalex.org/W2114054919","https://openalex.org/W2116361347","https://openalex.org/W2123162799","https://openalex.org/W2134086158","https://openalex.org/W2137226992","https://openalex.org/W2149298154","https://openalex.org/W2153635508","https://openalex.org/W2264003125","https://openalex.org/W2272544077","https://openalex.org/W2272985318","https://openalex.org/W2278544380","https://openalex.org/W2326591006","https://openalex.org/W2335107214","https://openalex.org/W2395665744","https://openalex.org/W2613181115","https://openalex.org/W3120421331","https://openalex.org/W4251179168","https://openalex.org/W6712604605"],"related_works":["https://openalex.org/W4389449520","https://openalex.org/W127192698","https://openalex.org/W2570600173","https://openalex.org/W2893008024","https://openalex.org/W2743735673","https://openalex.org/W4361801939","https://openalex.org/W2360131081","https://openalex.org/W2985941356","https://openalex.org/W2802243998","https://openalex.org/W1521014365"],"abstract_inverted_index":{"Data":[0],"streams":[1,12],"are":[2,62,176,184,285],"rapidly":[3,9],"and":[4,49,76,98,110,119,150,153,180,204,237,276,279],"constantly":[5,57],"growing.":[6],"Analysis":[7],"of":[8,19,38,68,73,86,94,174,182,198,226,261,282,290,303,311],"changing":[10],"data":[11,20,59,74,87,127,132,138,160,165,169,190,212,233,245,264,291,304],"is":[13,133,250],"quite":[14],"difficult":[15],"since":[16],"the":[17,36,43,52,66,69,71,84,92,113,126,158,177,185,211,227,254,301,309],"amount":[18],"increases":[21],"in":[22,171],"timely":[23],"manner.":[24],"Individual":[25],"patient":[26,53],"records":[27,54],"provide":[28],"a":[29,137,142,231,257,274],"vital":[30],"resource":[31],"for":[32,35,222],"health":[33],"research":[34],"benefit":[37],"society,":[39],"such":[40],"as":[41],"understanding":[42],"association":[44],"between":[45,116],"human":[46],"immune":[47,117],"system":[48,118],"viruses.":[50],"As":[51],"have":[55,219],"been":[56,220],"growing,":[58],"reduction":[60],"techniques":[61],"needed":[63],"to":[64,77,90,111,124,135,201,243,253,266],"reduce":[65,300,308],"complexity":[67],"data,":[70],"cost":[72,310],"storage":[75],"enhance":[78],"generalization":[79],"performance.":[80],"This":[81],"study":[82],"uses":[83],"concept":[85],"stream":[88,128],"mining":[89,129],"predict":[91],"effect":[93],"antibody":[95,194],"features":[96,195,199],"(IgGs)":[97],"primary":[99],"Natural":[100],"Killing":[101],"(NK)":[102],"cells'":[103],"cytotoxic":[104],"activities":[105],"on":[106],"RV144":[107,163,244],"vaccine":[108,164,186],"receipts":[109],"disclose":[112],"functional":[114],"relationship":[115],"HV":[120],"virus.":[121],"In":[122,229],"order":[123],"adapt":[125],"techniques,":[130],"this":[131],"manumitted":[134],"mimic":[136],"stream.":[139],"We":[140],"propose":[141],"novel":[143],"instance":[144],"selection":[145],"framework":[146,296],"that":[147,196],"identifies":[148],"relevant":[149,278],"important":[151,280],"instances":[152,281],"yields":[154],"better":[155],"results":[156],"than":[157],"entire":[159,263],"set.":[161,246],"The":[162],"set":[166,234,265,305],"contains":[167],"100":[168],"samples":[170,179,284],"which":[172,218],"20":[173],"them":[175,183],"placebo":[178],"80":[181],"injected":[187],"samples.":[188],"Each":[189],"sample":[191],"has":[192,292],"twenty":[193],"consist":[197],"related":[200],"IgG":[202],"subclass":[203],"antigen":[205],"specificity.":[206],"To":[207],"accomplish":[208],"our":[209,295],"goal":[210],"randomly":[213],"divided":[214,238],"into":[215,239],"four":[216],"chunks":[217,241],"utilised":[221,270],"sequential":[223],"random":[224],"sampling":[225],"data.":[228],"addition,":[230],"synthetic":[232],"was":[235],"created":[236],"five":[240],"similar":[242],"Then":[247],"each":[248],"chunk":[249,272,289],"sequentially":[251],"added":[252],"database":[255],"at":[256,273],"time.":[258],"However,":[259],"instead":[260],"using":[262],"select":[267],"samples,":[268],"we":[269],"one":[271],"time":[275],"most":[277],"upcoming":[283],"selected":[286],"before":[287],"new":[288],"arrived.":[293],"Therefore,":[294],"does":[297],"not":[298],"only":[299],"size":[302],"but":[306],"also":[307],"storage.":[312]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
