{"id":"https://openalex.org/W2166573308","doi":"https://doi.org/10.1145/1868328.1868335","title":"How effective is Tabu search to configure support vector regression for effort estimation?","display_name":"How effective is Tabu search to configure support vector regression for effort estimation?","publication_year":2010,"publication_date":"2010-09-12","ids":{"openalex":"https://openalex.org/W2166573308","doi":"https://doi.org/10.1145/1868328.1868335","mag":"2166573308"},"language":"en","primary_location":{"id":"doi:10.1145/1868328.1868335","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1868328.1868335","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Predictive Models in Software Engineering","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/A5064332237","display_name":"Anna Corazza","orcid":"https://orcid.org/0000-0002-9156-5079"},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"A. Corazza","raw_affiliation_strings":["University of Napoli \"Federico II\", Napoli, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Napoli \"Federico II\", Napoli, Italy","institution_ids":["https://openalex.org/I71267560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106313970","display_name":"Sergio Di Martino","orcid":"https://orcid.org/0000-0002-1019-9004"},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"S. Di Martino","raw_affiliation_strings":["University of Napoli \"Federico II\", Napoli, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Napoli \"Federico II\", Napoli, Italy","institution_ids":["https://openalex.org/I71267560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053084752","display_name":"Filomena Ferrucci","orcid":"https://orcid.org/0000-0002-0975-8972"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"F. Ferrucci","raw_affiliation_strings":["University of Salerno, Fisciano (SA), Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Salerno, Fisciano (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012888719","display_name":"Carmine Gravino","orcid":"https://orcid.org/0000-0002-4394-9035"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"C. Gravino","raw_affiliation_strings":["University of Salerno, Fisciano (SA), Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Salerno, Fisciano (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012165852","display_name":"Federica Sarro","orcid":"https://orcid.org/0000-0002-9146-442X"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"F. Sarro","raw_affiliation_strings":["University of Salerno, Fisciano (SA), Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Salerno, Fisciano (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085558039","display_name":"E. Mendes","orcid":"https://orcid.org/0000-0002-3859-3548"},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"E. Mendes","raw_affiliation_strings":["University of Auckland, Auckland, New Zeland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Auckland, Auckland, New Zeland","institution_ids":["https://openalex.org/I154130895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":11.418,"has_fulltext":false,"cited_by_count":62,"citation_normalized_percentile":{"value":0.98248012,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9965999722480774,"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"}},"topics":[{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9965999722480774,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9894999861717224,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9869999885559082,"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":0.7181037068367004},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7160856127738953},{"id":"https://openalex.org/keywords/tabu-search","display_name":"Tabu search","score":0.6624107956886292},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5895965695381165},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5826842188835144},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5707650184631348},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5537155270576477},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4874153435230255},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.47348082065582275},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4588907063007355},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.452881395816803},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4437127113342285},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14247724413871765},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1024397611618042}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7181037068367004},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7160856127738953},{"id":"https://openalex.org/C123370116","wikidata":"https://www.wikidata.org/wiki/Q1424540","display_name":"Tabu search","level":2,"score":0.6624107956886292},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5895965695381165},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5826842188835144},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5707650184631348},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5537155270576477},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4874153435230255},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.47348082065582275},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4588907063007355},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.452881395816803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4437127113342285},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14247724413871765},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1024397611618042},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1868328.1868335","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1868328.1868335","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Predictive Models in Software Engineering","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:1380092","is_oa":false,"landing_page_url":"http://discovery.ucl.ac.uk/1380092/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"     In:       (2010)     ","raw_type":"Proceedings paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320324133","display_name":"Universit\u00e0 degli Studi di Salerno","ror":"https://ror.org/0192m2k53"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W56743589","https://openalex.org/W409166618","https://openalex.org/W1560724230","https://openalex.org/W1575961892","https://openalex.org/W1818085238","https://openalex.org/W1964357740","https://openalex.org/W1973434865","https://openalex.org/W1987979080","https://openalex.org/W1997406557","https://openalex.org/W2009332873","https://openalex.org/W2020832745","https://openalex.org/W2022537368","https://openalex.org/W2024284172","https://openalex.org/W2039182691","https://openalex.org/W2044088589","https://openalex.org/W2100164091","https://openalex.org/W2102899008","https://openalex.org/W2104980832","https://openalex.org/W2118115183","https://openalex.org/W2119821739","https://openalex.org/W2125231355","https://openalex.org/W2125791732","https://openalex.org/W2135452472","https://openalex.org/W2143628522","https://openalex.org/W2146382566","https://openalex.org/W2154732019","https://openalex.org/W2156909104","https://openalex.org/W2161074247","https://openalex.org/W2168029744","https://openalex.org/W2339500526","https://openalex.org/W3023786531","https://openalex.org/W3101749733","https://openalex.org/W6780376396"],"related_works":["https://openalex.org/W2224940485","https://openalex.org/W2168643831","https://openalex.org/W2075514833","https://openalex.org/W2381791171","https://openalex.org/W4247343174","https://openalex.org/W1987877777","https://openalex.org/W2366189044","https://openalex.org/W2365741636","https://openalex.org/W2011733276","https://openalex.org/W4231225946"],"abstract_inverted_index":{"Background.":[0],"Recent":[1],"studies":[2],"have":[3,66],"shown":[4],"that":[5,29,179,188,242,296],"Support":[6],"Vector":[7],"Regression":[8],"(SVR)":[9],"has":[10],"an":[11,71,217],"interesting":[12,285],"potential":[13],"in":[14,61,74,140],"the":[15,32,49,52,58,68,127,132,155,189,208,221,245,248,254,260,263,270,289,294],"field":[16],"of":[17,51,70,83,154,185,191,207,220,291],"effort":[18,89,142,300],"estimation.":[19,90],"However":[20],"applying":[21],"SVR":[22,77,112,194,292],"requires":[23],"to":[24,40,78,85,104,163,214,224,266,287],"carefully":[25],"set":[26,54],"some":[27],"parameters":[28,84,222],"heavily":[30],"affect":[31],"prediction":[33,233],"accuracy.":[34],"No":[35],"general":[36],"guidelines":[37],"are":[38,161,239,251,253,283,297],"available":[39],"select":[41,79],"these":[42],"parameters,":[43,186],"whose":[44],"choice":[45,184,219],"also":[46],"depends":[47],"on":[48,200,232,259,278],"characteristics":[50],"data":[53,128,156,202],"used.":[55],"This":[56,91],"motivates":[57],"work":[59],"described":[60],"this":[62,201,243],"paper.":[63],"Aims.":[64],"We":[65,110],"investigated":[67],"use":[69,206,290],"optimization":[72,107],"technique":[73,92,198],"combination":[75,190],"with":[76,113,166],"a":[80,100,147,182,229,305],"suitable":[81,298],"subset":[82],"be":[86,276],"used":[87,103,119],"for":[88,126,235,299],"is":[93,99,137,244],"named":[94],"Tabu":[95,210],"Search":[96,211],"(TS),":[97],"which":[98,136],"meta-heuristic":[101,209],"approach":[102],"address":[105],"several":[106],"problems.":[108],"Method.":[109],"employed":[111,131],"linear":[114],"and":[115,118,145,172,193,227],"RBF":[116],"kernels,":[117],"variables'":[120],"preprocessing":[121],"strategies":[122],"(i.e.,":[123],"logarithmic).":[124],"As":[125,158],"set,":[129],"we":[130,238,250],"Tukutuku":[133],"cross-company":[134,306],"database,":[135],"widely":[138],"adopted":[139],"Web":[141],"estimation":[143],"studies,":[144],"performed":[146],"hold-out":[148],"validation":[149],"using":[150,304],"two":[151],"different":[152],"splits":[153],"set.":[157,203],"benchmark,":[159],"results":[160,177,249,272],"compared":[162],"those":[164],"obtained":[165,258],"Manual":[167],"StepWise":[168],"Regression,":[169],"Case-Based":[170],"Reasoning,":[171],"Bayesian":[173],"Networks.":[174],"Results.":[175],"Our":[176],"show":[178],"TS":[180,192],"provides":[181],"good":[183],"so":[187],"outperforms":[195],"any":[196],"other":[197],"applied":[199],"Conclusions.":[204],"The":[205],"allowed":[212],"us":[213],"obtain":[215],"(I)":[216],"automatic":[218],"required":[223],"run":[225],"SVR,":[226],"(II)":[228],"significant":[230],"improvement":[231],"accuracy":[234],"SVR.":[236],"While":[237],"not":[240],"guaranteed":[241],"global":[246],"optimum,":[247],"presenting":[252],"best":[255],"performance":[256],"ever":[257],"problem":[261],"at":[262],"hand,":[264],"up":[265],"now.":[267],"Of":[268],"course,":[269],"experimental":[271],"here":[273],"presented":[274],"should":[275],"assessed":[277],"further":[279],"data.":[280],"However,":[281],"they":[282],"surely":[284],"enough":[286],"suggest":[288],"among":[293],"techniques":[295],"estimation,":[301],"especially":[302],"when":[303],"database.":[307]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":6}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}