{"id":"https://openalex.org/W2914368787","doi":"https://doi.org/10.1109/ssci.2018.8628763","title":"Parallelization of Multi-label classification for large data sets","display_name":"Parallelization of Multi-label classification for large data sets","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2914368787","doi":"https://doi.org/10.1109/ssci.2018.8628763","mag":"2914368787"},"language":"en","primary_location":{"id":"doi:10.1109/ssci.2018.8628763","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2018.8628763","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Symposium Series on Computational Intelligence (SSCI)","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/A5022021020","display_name":"Shinjini Biswas","orcid":null},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shinjini Biswas","raw_affiliation_strings":["Computer Science and Automation, Indian Institute of Science, Bangalore, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Automation, Indian Institute of Science, Bangalore, India","institution_ids":["https://openalex.org/I59270414"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101879348","display_name":"V. Susheela Devi","orcid":"https://orcid.org/0000-0003-1001-7714"},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"V. Susheela Devi","raw_affiliation_strings":["Computer Science and Automation, Indian Institute of Science, Bangalore, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Automation, Indian Institute of Science, Bangalore, India","institution_ids":["https://openalex.org/I59270414"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.169,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.63428173,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"16","issue":null,"first_page":"2005","last_page":"2010"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9997000098228455,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9997000098228455,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9779000282287598,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.830956220626831},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.7464618682861328},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6579192876815796},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6005727648735046},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5509341359138489},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5183081030845642},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.5065795183181763},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.49801039695739746},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4695870280265808},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4649542570114136},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4476828873157501},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4436839818954468},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4433704614639282},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4349023401737213},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42522433400154114},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.18854960799217224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.830956220626831},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.7464618682861328},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6579192876815796},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6005727648735046},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5509341359138489},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5183081030845642},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.5065795183181763},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.49801039695739746},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4695870280265808},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4649542570114136},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4476828873157501},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4436839818954468},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4433704614639282},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4349023401737213},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42522433400154114},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.18854960799217224},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/ssci.2018.8628763","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2018.8628763","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.iisc.ac.in:62090","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196309","display_name":"NOT FOUND REPOSITORY (Indian Institute of Science Bangalore)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59270414","host_organization_name":"Indian Institute of Science Bangalore","host_organization_lineage":["https://openalex.org/I59270414"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"},{"id":"pmh:oai:eprints.iisc.ac.in:61956","is_oa":false,"landing_page_url":"http://eprints.iisc.ac.in/61956/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401429","display_name":"ePrints@IISc (Indian Institute of Science)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59270414","host_organization_name":"Indian Institute of Science Bangalore","host_organization_lineage":["https://openalex.org/I59270414"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceedings"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5400000214576721}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W146125889","https://openalex.org/W254202083","https://openalex.org/W831714202","https://openalex.org/W1546584168","https://openalex.org/W1965670643","https://openalex.org/W1972490990","https://openalex.org/W2001619934","https://openalex.org/W2027266161","https://openalex.org/W2052684427","https://openalex.org/W2061351061","https://openalex.org/W2067173300","https://openalex.org/W2100235303","https://openalex.org/W2123217057","https://openalex.org/W2136661605","https://openalex.org/W2138290126","https://openalex.org/W2146241755","https://openalex.org/W2156935079","https://openalex.org/W2173213060","https://openalex.org/W2498916464","https://openalex.org/W4206188021","https://openalex.org/W4285719527","https://openalex.org/W6609644794","https://openalex.org/W6666040507"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W2164382479","https://openalex.org/W2146343568","https://openalex.org/W98480971","https://openalex.org/W2150291671","https://openalex.org/W2013643406","https://openalex.org/W2027972911","https://openalex.org/W2157978810","https://openalex.org/W2597809628","https://openalex.org/W1972401983"],"abstract_inverted_index":{"Over":[0],"the":[1,28,84,99,120,134,146,150,157,163,170,189],"last":[2],"few":[3],"years,":[4],"multi-label":[5,70,90,158,178],"learning":[6],"has":[7],"received":[8],"a":[9,18,33,39,52,60,89,95,114,138],"lot":[10],"of":[11,63,76,88,101,122,130,156,165,183,188],"attention":[12],"in":[13,74,113,181],"research":[14],"and":[15,66,78,86,148,186],"industries.":[16],"Since":[17],"pattern":[19],"can":[20,97],"belong":[21],"to":[22,37,55,82,144],"more":[23],"than":[24],"one":[25],"class":[26],"at":[27],"same":[29],"time,":[30],"it":[31,103],"is":[32,59],"very":[34,127],"challenging":[35],"task":[36],"classify":[38],"test":[40],"pattern.":[41],"Multi-label":[42],"classification":[43,71,91,159],"algorithms":[44],"while":[45],"inferring":[46],"on":[47],"large":[48,107,123,128],"data":[49,108,124,179],"sets":[50,125],"take":[51],"long":[53],"time":[54,151],"run.":[56],"So,":[57],"there":[58],"growing":[61],"demand":[62],"an":[64],"effective":[65],"efficient":[67],"method":[68,141],"for":[69,106,153],"problems,":[72],"both":[73,184],"terms":[75,182],"accuracy":[77,87,147,185],"speed.":[79],"We":[80,117],"endeavour":[81],"improve":[83,145],"performance":[85],"algorithm":[92],"which,":[93],"given":[94],"pattern,":[96],"predict":[98],"set":[100],"labels":[102],"belongs":[104],"to,":[105],"sets,":[109,180],"using":[110,137,166],"parallel":[111,167],"computing":[112],"distributed":[115],"manner.":[116],"also":[118],"reduced":[119],"dimensionality":[121],"with":[126],"number":[129],"features":[131,136],"by":[132],"removing":[133],"redundant":[135],"feature":[139],"selection":[140],"(Fscore)":[142],"[1]":[143],"reduce":[149],"taken":[152],"training":[154],"phase":[155],"algorithm.The":[160],"result":[161],"shows":[162],"benefits":[164],"processing":[168],"over":[169,175],"traditional":[171],"single-node":[172],"execution,":[173],"tested":[174],"five":[176],"benchmark":[177],"speedup":[187],"process.":[190]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
