{"id":"https://openalex.org/W1894550771","doi":"https://doi.org/10.1109/esem.2015.7321199","title":"How to Make Best Use of Cross-Company Data for Web Effort Estimation?","display_name":"How to Make Best Use of Cross-Company Data for Web Effort Estimation?","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W1894550771","doi":"https://doi.org/10.1109/esem.2015.7321199","mag":"1894550771"},"language":"en","primary_location":{"id":"doi:10.1109/esem.2015.7321199","is_oa":false,"landing_page_url":"https://doi.org/10.1109/esem.2015.7321199","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/2381/35961","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064089961","display_name":"Leandro L. Minku","orcid":"https://orcid.org/0000-0002-2639-0671"},"institutions":[{"id":"https://openalex.org/I153648349","display_name":"University of Leicester","ror":"https://ror.org/04h699437","country_code":"GB","type":"education","lineage":["https://openalex.org/I153648349"]},{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Leandro Minku","raw_affiliation_strings":["Department of Computer Science, University of Leicester, UK","School of Computer Science, University of Birmingham, Birmingham, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Leicester, UK","institution_ids":["https://openalex.org/I153648349"]},{"raw_affiliation_string":"School of Computer Science, University of Birmingham, Birmingham, UK","institution_ids":["https://openalex.org/I79619799"]}]},{"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/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]},{"id":"https://openalex.org/I52719799","display_name":"Blekinge Institute of Technology","ror":"https://ror.org/0093a8w51","country_code":"SE","type":"education","lineage":["https://openalex.org/I52719799"]}],"countries":["GB","SE"],"is_corresponding":false,"raw_author_name":"Federica Sarro","raw_affiliation_strings":["Department of Computer Science, Blekinge Institute Technology, Sweden, UK","Dept. of Comput. Sci., Univ. Coll. London, London, UK#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Blekinge Institute Technology, Sweden, UK","institution_ids":["https://openalex.org/I52719799"]},{"raw_affiliation_string":"Dept. of Comput. Sci., Univ. Coll. London, London, UK#TAB#","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103878525","display_name":"Em\u00edlia Mendes","orcid":null},"institutions":[{"id":"https://openalex.org/I52719799","display_name":"Blekinge Institute of Technology","ror":"https://ror.org/0093a8w51","country_code":"SE","type":"education","lineage":["https://openalex.org/I52719799"]},{"id":"https://openalex.org/I98381234","display_name":"University of Oulu","ror":"https://ror.org/03yj89h83","country_code":"FI","type":"education","lineage":["https://openalex.org/I98381234"]}],"countries":["FI","SE"],"is_corresponding":false,"raw_author_name":"Emilia Mendes","raw_affiliation_strings":["University of Oulu, Finland","Blekinge Inst. Technol., Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Oulu, Finland","institution_ids":["https://openalex.org/I98381234"]},{"raw_affiliation_string":"Blekinge Inst. Technol., Sweden","institution_ids":["https://openalex.org/I52719799"]}]},{"author_position":"last","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":"Filomena Ferrucci","raw_affiliation_strings":["Department of Computer Science, University of Salerno, Italy","Department of Computer Science, University of Salerno, Salerno, Italy#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Salerno, Italy","institution_ids":["https://openalex.org/I131729948"]},{"raw_affiliation_string":"Department of Computer Science, University of Salerno, Salerno, Italy#TAB#","institution_ids":["https://openalex.org/I131729948"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":29,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"se 4","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":1.0,"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":1.0,"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/T12127","display_name":"Software System Performance and Reliability","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10430","display_name":"Software Engineering Techniques and Practices","score":0.986299991607666,"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":0.727056622505188},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6463178396224976},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.5355472564697266},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.5261951088905334},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.509652853012085},{"id":"https://openalex.org/keywords/web-application","display_name":"Web application","score":0.5018594264984131},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.47784730792045593},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.4620484709739685},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39658087491989136},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3947686553001404},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.27240699529647827},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.21658265590667725},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18148311972618103}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.727056622505188},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6463178396224976},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.5355472564697266},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.5261951088905334},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.509652853012085},{"id":"https://openalex.org/C118643609","wikidata":"https://www.wikidata.org/wiki/Q189210","display_name":"Web application","level":2,"score":0.5018594264984131},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.47784730792045593},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.4620484709739685},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39658087491989136},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3947686553001404},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.27240699529647827},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.21658265590667725},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18148311972618103},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.1109/esem.2015.7321199","is_oa":false,"landing_page_url":"https://doi.org/10.1109/esem.2015.7321199","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/8c1e76c0-7715-45d1-acbd-b5b4879b7210","is_oa":true,"landing_page_url":"http://www.scopus.com/inward/record.url?scp=84961620838&partnerID=8YFLogxK","pdf_url":"http://hdl.handle.net/2381/35961","source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Minku, L, Sarro, F, Mendes, E & Ferrucci, F 2015, How to Make Best Use of Cross-Company Data for Web Effort Estimation? in Proceedings of the 9th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). vol. 2015-November, 7321199, IEEE Xplore, Beijing, China, pp. 172-181, ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2015, Beijing, China, 22/10/15. https://doi.org/10.1109/ESEM.2015.7321199","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.703.1009","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.703.1009","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www0.cs.ucl.ac.uk/staff/F.Sarro/resource/papers/esem15.pdf","raw_type":"text"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:1538187","is_oa":false,"landing_page_url":"http://discovery.ucl.ac.uk/1538187/","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: (pp. p. 10). (2015)","raw_type":"Proceedings paper"},{"id":"pmh:oai:figshare.com:article/10170767","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/How_to_Make_Best_Use_of_Cross-Company_Data_for_Web_Effort_Estimation_/10170767","pdf_url":null,"source":{"id":"https://openalex.org/S4306402621","display_name":"INDIGO (University of Illinois at Chicago)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39422238","host_organization_name":"University of Illinois Chicago","host_organization_lineage":["https://openalex.org/I39422238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference contribution"},{"id":"pmh:oai:lra.le.ac.uk:2381/35961","is_oa":false,"landing_page_url":"http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7321199&amp;filter%3DAND%28p_IS_Number%3A7321177%29","pdf_url":null,"source":{"id":"https://openalex.org/S4306402365","display_name":"Leicester Research Archive (University of Leicester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I153648349","host_organization_name":"University of Leicester","host_organization_lineage":["https://openalex.org/I153648349"],"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 Paper"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/8c1e76c0-7715-45d1-acbd-b5b4879b7210","is_oa":false,"landing_page_url":"https://research.birmingham.ac.uk/en/publications/8c1e76c0-7715-45d1-acbd-b5b4879b7210","pdf_url":null,"source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Minku, L, Sarro, F, Mendes, E & Ferrucci, F 2015, How to Make Best Use of Cross-Company Data for Web Effort Estimation? in Proceedings of the 9th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). vol. 2015-November, 7321199, IEEE Xplore, Beijing, China, pp. 172-181, ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2015, Beijing, China, 22/10/15. https://doi.org/10.1109/ESEM.2015.7321199","raw_type":"contributionToPeriodical"}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:publications/8c1e76c0-7715-45d1-acbd-b5b4879b7210","is_oa":true,"landing_page_url":"http://www.scopus.com/inward/record.url?scp=84961620838&partnerID=8YFLogxK","pdf_url":"http://hdl.handle.net/2381/35961","source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Minku, L, Sarro, F, Mendes, E & Ferrucci, F 2015, How to Make Best Use of Cross-Company Data for Web Effort Estimation? in Proceedings of the 9th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). vol. 2015-November, 7321199, IEEE Xplore, Beijing, China, pp. 172-181, ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2015, Beijing, China, 22/10/15. https://doi.org/10.1109/ESEM.2015.7321199","raw_type":"contributionToPeriodical"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G6794522244","display_name":null,"funder_award_id":"EP/J017515/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W1894550771.pdf"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W16287042","https://openalex.org/W165207608","https://openalex.org/W1500321873","https://openalex.org/W1522987989","https://openalex.org/W1579827372","https://openalex.org/W1673174959","https://openalex.org/W1965441902","https://openalex.org/W1968135603","https://openalex.org/W1970660793","https://openalex.org/W1989354793","https://openalex.org/W1990537706","https://openalex.org/W1997406557","https://openalex.org/W2000642745","https://openalex.org/W2009332873","https://openalex.org/W2029697032","https://openalex.org/W2044467713","https://openalex.org/W2063876764","https://openalex.org/W2068816944","https://openalex.org/W2073751151","https://openalex.org/W2081004173","https://openalex.org/W2091235628","https://openalex.org/W2097670073","https://openalex.org/W2104378021","https://openalex.org/W2104789242","https://openalex.org/W2133990480","https://openalex.org/W2162373602","https://openalex.org/W2166573308","https://openalex.org/W2171816001","https://openalex.org/W2318989318","https://openalex.org/W2499806419","https://openalex.org/W4206457894","https://openalex.org/W4241607863","https://openalex.org/W4285719527","https://openalex.org/W6600653409","https://openalex.org/W6606806422","https://openalex.org/W6630072617","https://openalex.org/W6673363746","https://openalex.org/W6723832736"],"related_works":["https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W2372385138","https://openalex.org/W4296359239","https://openalex.org/W1557905920","https://openalex.org/W2043093291","https://openalex.org/W4282583532"],"abstract_inverted_index":{"[Context]:":[0],"The":[1],"numerous":[2],"challenges":[3],"that":[4,58,170,228,250],"can":[5],"hinder":[6],"software":[7,30,273],"companies":[8,142],"from":[9,139,186],"gathering":[10],"their":[11],"own":[12],"data":[13,77,84,122,242],"have":[14],"motivated":[15],"over":[16,225],"the":[17,23,43,48,75,81,91,117,126,130,145,175,187,215,230,240,251],"past":[18],"15":[19],"years":[20],"research":[21,36],"on":[22,38,135],"use":[24,92,231,252],"of":[25,34,50,54,93,144,174,214,232,253],"cross-company":[26],"(CC)":[27],"datasets":[28,111],"for":[29,243,255],"effort":[31,40,106,245,257],"prediction.":[32],"Part":[33],"this":[35],"focused":[37],"Web":[39,51,105,137,244,256],"prediction,":[41],"given":[42],"large":[44],"increase":[45],"worldwide":[46],"in":[47,114,263],"development":[49],"applications.":[52],"Some":[53],"these":[55,156],"studies":[56,227],"indicate":[57],"it":[59],"may":[60],"be":[61],"possible":[62],"to":[63,73,80,100,102,116,129,150,200,235,239,271],"achieve":[64,201],"better":[65,204],"performance":[66,205],"using":[67,109,120,211],"CC":[68,76,110,127,184,237],"models":[69,128,157,160,238],"if":[70],"some":[71],"strategy":[72],"make":[74],"more":[78],"similar":[79,202],"within-company":[82],"(WC)":[83],"is":[85,259],"adopted.":[86],"[Goal]:":[87],"This":[88],"study":[89],"investigates":[90],"a":[94,166,182,192,207],"recently":[95],"proposed":[96],"approach":[97,185],"called":[98],"Dycom":[99,180,197,254,270],"assess":[101],"what":[103],"extent":[104],"predictions":[107,118],"obtained":[108,119],"are":[112,221],"effective":[113],"relation":[115],"WC":[121,131,167,208,216,241],"when":[123,268],"explicitly":[124],"mapping":[125],"context.":[132],"[Method]:":[133],"Data":[134],"125":[136],"projects":[138],"eight":[140],"different":[141,233],"part":[143],"Tukutuku":[146],"database":[147],"were":[148],"used":[149],"build":[151],"prediction":[152,258],"models.":[153],"We":[154,177,190,248],"benchmarked":[155],"against":[158,181],"baseline":[159],"(mean":[161],"and":[162,165,262],"median":[163],"effort)":[164],"base":[168],"learner":[169],"does":[171],"not":[172],"benefit":[173],"mapping.":[176],"also":[178,222],"compared":[179],"competitive":[183],"literature":[188],"(NN-filtering).":[189],"report":[191],"company-by-":[193],"company":[194],"analysis.":[195],"[Results]:":[196],"usually":[198],"managed":[199],"or":[203],"than":[206],"model":[209],"while":[210],"only":[212],"half":[213],"training":[217],"data.":[218],"These":[219],"results":[220,267],"an":[223],"improvement":[224],"previous":[226,266],"investigated":[229],"strategies":[234],"adapt":[236],"estimation.":[246],"[Conclusions]:":[247],"conclude":[249],"quite":[260],"promising":[261],"general":[264],"supports":[265],"applying":[269],"conventional":[272],"datasets.":[274]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2}],"updated_date":"2026-07-19T07:52:34.831488","created_date":"2025-10-10T00:00:00"}
