{"id":"https://openalex.org/W2904368497","doi":"https://doi.org/10.1145/3229783.3229805","title":"SEET","display_name":"SEET","publication_year":2018,"publication_date":"2018-12-07","ids":{"openalex":"https://openalex.org/W2904368497","doi":"https://doi.org/10.1145/3229783.3229805","mag":"2904368497"},"language":"en","primary_location":{"id":"doi:10.1145/3229783.3229805","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3229783.3229805","pdf_url":null,"source":{"id":"https://openalex.org/S186921487","display_name":"ACM SIGSOFT Software Engineering Notes","issn_l":"0163-5948","issn":["0163-5948","1943-5843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM SIGSOFT Software Engineering Notes","raw_type":"journal-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/A5035539513","display_name":"Tirimula Rao Benala","orcid":"https://orcid.org/0000-0002-0613-9893"},"institutions":[{"id":"https://openalex.org/I142809039","display_name":"Jawaharlal Nehru Technological University, Kakinada","ror":"https://ror.org/05s9t8c95","country_code":"IN","type":"education","lineage":["https://openalex.org/I142809039"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Tirimula Rao Benala1","raw_affiliation_strings":["JNTUK University College of Engineering, AP, India"],"affiliations":[{"raw_affiliation_string":"JNTUK University College of Engineering, AP, India","institution_ids":["https://openalex.org/I142809039"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105166983","display_name":"Rajib Mall","orcid":null},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajib Mall","raw_affiliation_strings":["Indian Institute of Technology, Kharagpur, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5035539513"],"corresponding_institution_ids":["https://openalex.org/I142809039"],"apc_list":null,"apc_paid":null,"fwci":0.1692,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.62441706,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"43","issue":"3","first_page":"17","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9973999857902527,"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":0.9973999857902527,"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/T10260","display_name":"Software Engineering Research","score":0.9930999875068665,"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"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.968500018119812,"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/ensemble-learning","display_name":"Ensemble learning","score":0.7435124516487122},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6874459981918335},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6639057993888855},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6349067687988281},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6108001470565796},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6098890900611877},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.5706713199615479},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.43801456689834595},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38623249530792236},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.20430532097816467},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13176825642585754},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10416507720947266}],"concepts":[{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.7435124516487122},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6874459981918335},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6639057993888855},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6349067687988281},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6108001470565796},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6098890900611877},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.5706713199615479},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.43801456689834595},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38623249530792236},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.20430532097816467},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13176825642585754},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10416507720947266}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3229783.3229805","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3229783.3229805","pdf_url":null,"source":{"id":"https://openalex.org/S186921487","display_name":"ACM SIGSOFT Software Engineering Notes","issn_l":"0163-5948","issn":["0163-5948","1943-5843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM SIGSOFT Software Engineering Notes","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W409166618","https://openalex.org/W881651986","https://openalex.org/W1605688901","https://openalex.org/W1970660793","https://openalex.org/W1978453247","https://openalex.org/W1982160761","https://openalex.org/W1993694224","https://openalex.org/W2004141087","https://openalex.org/W2009151039","https://openalex.org/W2009407457","https://openalex.org/W2011533104","https://openalex.org/W2037557484","https://openalex.org/W2037664399","https://openalex.org/W2061082730","https://openalex.org/W2070567333","https://openalex.org/W2078619386","https://openalex.org/W2097670073","https://openalex.org/W2103296684","https://openalex.org/W2104236502","https://openalex.org/W2104615423","https://openalex.org/W2106525823","https://openalex.org/W2111072639","https://openalex.org/W2123279272","https://openalex.org/W2124116645","https://openalex.org/W2125791732","https://openalex.org/W2131378644","https://openalex.org/W2157177276","https://openalex.org/W2171816001","https://openalex.org/W2567530267","https://openalex.org/W2605932792","https://openalex.org/W2912934387"],"related_works":["https://openalex.org/W2794896638","https://openalex.org/W1807784185","https://openalex.org/W4390905871","https://openalex.org/W3202800081","https://openalex.org/W1909207154","https://openalex.org/W4322009192","https://openalex.org/W4320483926","https://openalex.org/W3124390867","https://openalex.org/W3101614107","https://openalex.org/W3204228978"],"abstract_inverted_index":{"Software":[0],"development":[1],"effort":[2],"estimation":[3],"(SDEE)":[4],"is":[5,60,161],"a":[6,48,139,144,152],"significant":[7],"activity":[8],"in":[9],"project":[10,18,35],"management":[11],"and":[12,25,98,122,163,202],"serves":[13],"as":[14,126,151],"the":[15,73,127,136,158],"basis":[16],"for":[17,71,195],"bidding,":[19],"planning,":[20],"staffing,":[21],"resource":[22],"allocation,":[23],"scheduling,":[24],"cost":[26],"estimation.":[27],"The":[28,54,155,179],"accuracy":[29,75,150],"of":[30,57,66,76,138,157],"SDEE":[31,52],"techniques":[32,129],"varies":[33],"from":[34],"to":[36,61,109,130,199],"project,":[37],"which":[38],"makes":[39],"them":[40],"rather":[41],"unreliable.":[42],"In":[43,78],"this":[44,58],"backdrop,":[45],"we":[46],"propose":[47],"foundation":[49],"centered":[50],"ensemble-based":[51],"approach.":[53],"primary":[55],"goal":[56],"approach":[59],"design":[62,142],"an":[63,111,132],"ensemble":[64,91,141,159,174,204],"consisting":[65],"different":[67],"machine":[68,88,96,116],"learning":[69,89,95,117],"methods":[70],"improving":[72],"prediction":[74],"SDEE.":[77],"recent":[79],"times,":[80],"several":[81],"research":[82],"results":[83,194],"have":[84,105],"been":[85,107],"reported":[86],"on":[87],"based":[90,171],"design,":[92],"but":[93],"extreme":[94],"(ELM)":[97],"least":[99],"square":[100,168],"support":[101],"vector":[102],"regression":[103],"(LSSVR)":[104],"not":[106],"used":[108],"develop":[110],"ensemble.":[112,133],"We":[113,134,191],"chose":[114],"three":[115],"techniques,":[118],"namely":[119],"ELM,":[120],"LSSVR,":[121],"multilayer":[123],"perceptron":[124],"(MLP)":[125],"base":[128,200],"build":[131],"investigated":[135],"performance":[137,156],"homogeneous":[140],"using":[143,184],"linear":[145],"combination":[146],"rule":[147],"with":[148,165,176],"standardized":[149],"weight":[153],"factor.":[154],"model":[160,175,197],"validated":[162],"compared":[164,198],"root":[166],"mean":[167],"error":[169],"(RMSE)":[170],"weighted":[172],"average":[173],"equivalent":[177],"configuration.":[178],"experimental":[180],"study":[181],"was":[182],"conducted":[183],"publicly":[185],"available":[186],"PROMISE":[187],"repository":[188],"test":[189],"suite.":[190],"achieved":[192],"promising":[193],"SEET":[196],"learners":[201],"RMSE":[203],"model.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-20T07:46:08.049788","created_date":"2018-12-22T00:00:00"}
