{"id":"https://openalex.org/W2599286794","doi":"https://doi.org/10.1587/transinf.2016dap0024","title":"A Novel Label Aggregation with Attenuated Scores for Ground-Truth Identification of Dataset Annotation with Crowdsourcing","display_name":"A Novel Label Aggregation with Attenuated Scores for Ground-Truth Identification of Dataset Annotation with Crowdsourcing","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2599286794","doi":"https://doi.org/10.1587/transinf.2016dap0024","mag":"2599286794"},"language":"en","primary_location":{"id":"doi:10.1587/transinf.2016dap0024","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2016dap0024","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E100.D/4/E100.D_2016DAP0024/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.jstage.jst.go.jp/article/transinf/E100.D/4/E100.D_2016DAP0024/_pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048883385","display_name":"Ratchainant Thammasudjarit","orcid":"https://orcid.org/0000-0002-1365-3428"},"institutions":[{"id":"https://openalex.org/I25399158","display_name":"Mahidol University","ror":"https://ror.org/01znkr924","country_code":"TH","type":"education","lineage":["https://openalex.org/I25399158"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Ratchainant THAMMASUDJARIT","raw_affiliation_strings":["Faculty of Information and Communication Technology, Mahidol University"],"affiliations":[{"raw_affiliation_string":"Faculty of Information and Communication Technology, Mahidol University","institution_ids":["https://openalex.org/I25399158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074458532","display_name":"Anon Plangprasopchok","orcid":"https://orcid.org/0000-0001-6659-580X"},"institutions":[{"id":"https://openalex.org/I14316845","display_name":"National Electronics and Computer Technology Center","ror":"https://ror.org/04z82ry91","country_code":"TH","type":"government","lineage":["https://openalex.org/I1332092204","https://openalex.org/I14316845"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Anon PLANGPRASOPCHOK","raw_affiliation_strings":["National Electronics and Computer Technology Center"],"affiliations":[{"raw_affiliation_string":"National Electronics and Computer Technology Center","institution_ids":["https://openalex.org/I14316845"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114257696","display_name":"Charnyote Pluempitiwiriyawej","orcid":null},"institutions":[{"id":"https://openalex.org/I25399158","display_name":"Mahidol University","ror":"https://ror.org/01znkr924","country_code":"TH","type":"education","lineage":["https://openalex.org/I25399158"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Charnyote PLUEMPITIWIRIYAWEJ","raw_affiliation_strings":["Faculty of Information and Communication Technology, Mahidol University"],"affiliations":[{"raw_affiliation_string":"Faculty of Information and Communication Technology, Mahidol University","institution_ids":["https://openalex.org/I25399158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5048883385"],"corresponding_institution_ids":["https://openalex.org/I25399158"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01994772,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"E100.D","issue":"4","first_page":"750","last_page":"757"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9914000034332275,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9692000150680542,"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":0.8746178150177002},{"id":"https://openalex.org/keywords/crowdsourcing","display_name":"Crowdsourcing","score":0.8559544086456299},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.8411276340484619},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.7133975028991699},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6902047395706177},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6003036499023438},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5819807052612305},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5705091953277588},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5191215872764587},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.48749423027038574},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4811588525772095},{"id":"https://openalex.org/keywords/majority-rule","display_name":"Majority rule","score":0.4397692084312439},{"id":"https://openalex.org/keywords/usable","display_name":"USable","score":0.4318321943283081},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.384613037109375},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3629143238067627},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32769477367401123}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8746178150177002},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.8559544086456299},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.8411276340484619},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.7133975028991699},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6902047395706177},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6003036499023438},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5819807052612305},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5705091953277588},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5191215872764587},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.48749423027038574},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4811588525772095},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.4397692084312439},{"id":"https://openalex.org/C2780615836","wikidata":"https://www.wikidata.org/wiki/Q2471869","display_name":"USable","level":2,"score":0.4318321943283081},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.384613037109375},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3629143238067627},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32769477367401123},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transinf.2016dap0024","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2016dap0024","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E100.D/4/E100.D_2016DAP0024/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1587/transinf.2016dap0024","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2016dap0024","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E100.D/4/E100.D_2016DAP0024/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2599286794.pdf","grobid_xml":"https://content.openalex.org/works/W2599286794.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W9014458","https://openalex.org/W1444168786","https://openalex.org/W1543648998","https://openalex.org/W1970381522","https://openalex.org/W2000244138","https://openalex.org/W2032740574","https://openalex.org/W2049633694","https://openalex.org/W2093825590","https://openalex.org/W2108598243","https://openalex.org/W2113878109","https://openalex.org/W2128475742","https://openalex.org/W2129345386","https://openalex.org/W2129494713","https://openalex.org/W2142518823","https://openalex.org/W2146928171","https://openalex.org/W2150612552","https://openalex.org/W2152009989","https://openalex.org/W2158880898","https://openalex.org/W2162815002","https://openalex.org/W2196604737","https://openalex.org/W2251818274"],"related_works":["https://openalex.org/W3032998312","https://openalex.org/W4384486036","https://openalex.org/W135177976","https://openalex.org/W1503094549","https://openalex.org/W2337920774","https://openalex.org/W2886410948","https://openalex.org/W2025875869","https://openalex.org/W2039876276","https://openalex.org/W2605569989","https://openalex.org/W2295086410"],"abstract_inverted_index":{"Ground-truth":[0],"identification":[1],"-":[2,18,107],"the":[3,7,25,35,75,92,98,159,167,182],"process,":[4],"which":[5,85],"infers":[6],"most":[8],"probable":[9],"labels,":[10,84],"for":[11,29,115,128,181],"a":[12,20,30,51,78,173],"certain":[13],"dataset,":[14],"from":[15,41],"crowdsourcing":[16],"annotations":[17,40],"is":[19,37,172],"crucial":[21],"task":[22],"to":[23,60,70,81],"make":[24],"dataset":[26],"usable,":[27],"e.g.,":[28],"supervised":[31],"learning":[32],"problem.":[33],"Nevertheless,":[34],"process":[36,76],"challenging":[38],"because":[39],"multiple":[42],"annotators":[43],"are":[44,68,86],"inconsistent":[45],"and":[46,120],"noisy.":[47],"Existing":[48],"methods":[49],"require":[50],"set":[52],"of":[53,117,158],"data":[54],"sample":[55],"with":[56],"corresponding":[57],"ground-truth":[58,129],"labels":[59,180],"precisely":[61],"estimate":[62],"annotator":[63,113],"performance":[64,114],"but":[65],"such":[66],"samples":[67],"difficult":[69],"obtain":[71],"in":[72,142,162],"practice.":[73],"Moreover,":[74],"requires":[77],"post-editing":[79,183],"step":[80],"validate":[82],"indefinite":[83,179],"generally":[87],"unidentifiable":[88],"without":[89],"thoroughly":[90],"inspecting":[91],"whole":[93],"annotated":[94],"data.":[95,165],"To":[96],"address":[97],"challenges,":[99],"this":[100],"paper":[101],"introduces:":[102],"1)":[103],"Attenuated":[104],"score":[105],"(A-score)":[106],"an":[108],"indicator":[109,175],"that":[110,125,135,170,176],"locally":[111],"measures":[112],"segments":[116],"annotation":[118],"sequences,":[119],"2)":[121],"label":[122,137],"aggregation":[123,138],"method":[124],"applies":[126],"A-score":[127,136,171],"identification.":[130],"The":[131],"experimental":[132],"results":[133,168],"demonstrate":[134],"outperforms":[139],"majority":[140],"vote":[141],"all":[143,163],"datasets":[144],"by":[145],"accurately":[146],"recovering":[147],"more":[148],"labels.":[149],"It":[150],"also":[151],"achieves":[152],"higher":[153],"F1":[154],"scores":[155],"than":[156],"those":[157],"strong":[160],"baselines":[161],"multi-class":[164],"Additionally,":[166],"suggest":[169],"promising":[174],"helps":[177],"identifying":[178],"procedure.":[184]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
