{"id":"https://openalex.org/W1967256553","doi":"https://doi.org/10.1109/re.2014.6912258","title":"Scaling requirements extraction to the crowd: Experiments with privacy policies","display_name":"Scaling requirements extraction to the crowd: Experiments with privacy policies","publication_year":2014,"publication_date":"2014-08-01","ids":{"openalex":"https://openalex.org/W1967256553","doi":"https://doi.org/10.1109/re.2014.6912258","mag":"1967256553"},"language":"en","primary_location":{"id":"doi:10.1109/re.2014.6912258","is_oa":false,"landing_page_url":"https://doi.org/10.1109/re.2014.6912258","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE 22nd International Requirements Engineering Conference (RE)","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/A5006266551","display_name":"Travis D. Breaux","orcid":"https://orcid.org/0000-0001-7127-8155"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Travis D. Breaux","raw_affiliation_strings":["Institute for Software Research, Carnegie Mellon University, Pittsburgh, Pennsylvania","[Institute for Software Research, Carnegie Mellon University, Pittsburgh, Pennsylvania United States]"],"affiliations":[{"raw_affiliation_string":"Institute for Software Research, Carnegie Mellon University, Pittsburgh, Pennsylvania","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"[Institute for Software Research, Carnegie Mellon University, Pittsburgh, Pennsylvania United States]","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061205711","display_name":"Florian Schaub","orcid":"https://orcid.org/0000-0003-1039-7155"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Florian Schaub","raw_affiliation_strings":["Institute for Software Research, Carnegie Mellon University, Pittsburgh, Pennsylvania","[Institute for Software Research, Carnegie Mellon University, Pittsburgh, Pennsylvania United States]"],"affiliations":[{"raw_affiliation_string":"Institute for Software Research, Carnegie Mellon University, Pittsburgh, Pennsylvania","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"[Institute for Software Research, Carnegie Mellon University, Pittsburgh, Pennsylvania United States]","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006266551"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":9.4757,"has_fulltext":false,"cited_by_count":49,"citation_normalized_percentile":{"value":0.97604906,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"163","last_page":"172"},"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/T11675","display_name":"Open Source Software Innovations","score":0.9947999715805054,"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/T10260","display_name":"Software Engineering Research","score":0.9914000034332275,"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":0.8169804811477661},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.7169961929321289},{"id":"https://openalex.org/keywords/crowdsourcing","display_name":"Crowdsourcing","score":0.6967207789421082},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.675227165222168},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.6708270907402039},{"id":"https://openalex.org/keywords/data-extraction","display_name":"Data extraction","score":0.5345280170440674},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4535171091556549},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4520556330680847},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3782092332839966},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3500092625617981},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3411230444908142},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3258640468120575},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.2721560001373291},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.15482497215270996},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10650837421417236}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8169804811477661},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.7169961929321289},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.6967207789421082},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.675227165222168},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.6708270907402039},{"id":"https://openalex.org/C2777466982","wikidata":"https://www.wikidata.org/wiki/Q5227287","display_name":"Data extraction","level":3,"score":0.5345280170440674},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4535171091556549},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4520556330680847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3782092332839966},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3500092625617981},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3411230444908142},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3258640468120575},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.2721560001373291},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.15482497215270996},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10650837421417236},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/re.2014.6912258","is_oa":false,"landing_page_url":"https://doi.org/10.1109/re.2014.6912258","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE 22nd International Requirements Engineering Conference (RE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.75,"id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1493372904","https://openalex.org/W1501025848","https://openalex.org/W1543648998","https://openalex.org/W1803273808","https://openalex.org/W1970381522","https://openalex.org/W1995790095","https://openalex.org/W2020740057","https://openalex.org/W2022710553","https://openalex.org/W2024166834","https://openalex.org/W2025765878","https://openalex.org/W2049774111","https://openalex.org/W2056426629","https://openalex.org/W2058179030","https://openalex.org/W2058738785","https://openalex.org/W2070248097","https://openalex.org/W2070504353","https://openalex.org/W2075876574","https://openalex.org/W2098865355","https://openalex.org/W2103362845","https://openalex.org/W2106568252","https://openalex.org/W2107930672","https://openalex.org/W2109021302","https://openalex.org/W2120396827","https://openalex.org/W2122987719","https://openalex.org/W2128830091","https://openalex.org/W2133485007","https://openalex.org/W2139735278","https://openalex.org/W2148479118","https://openalex.org/W2151401338","https://openalex.org/W2153880043","https://openalex.org/W2157582701","https://openalex.org/W2158821585","https://openalex.org/W2158880898","https://openalex.org/W2163361328","https://openalex.org/W2170989440","https://openalex.org/W3022452870","https://openalex.org/W3122078363","https://openalex.org/W3126123353","https://openalex.org/W4206070770","https://openalex.org/W4281564584","https://openalex.org/W6630087544","https://openalex.org/W6632436798","https://openalex.org/W6675559536","https://openalex.org/W6676470270","https://openalex.org/W6679599066","https://openalex.org/W6684172481","https://openalex.org/W7074706539"],"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/W4318823662","https://openalex.org/W3207526114","https://openalex.org/W2084164722"],"abstract_inverted_index":{"Natural":[0],"language":[1],"text":[2],"sources":[3],"have":[4],"increasingly":[5],"been":[6],"used":[7],"to":[8,33,47,67,75,83,109,117,147,154],"develop":[9],"new":[10,22],"methods":[11],"and":[12,16,44,59,98,106,130,143,164],"tools":[13],"for":[14,167],"extracting":[15,124],"analyzing":[17],"requirements.":[18],"To":[19,65],"validate":[20],"these":[21,91],"approaches,":[23],"researchers":[24],"rely":[25],"on":[26],"a":[27,35,78,84,144,150,175,185],"small":[28],"number":[29,86],"of":[30,39,56,63,87,113,123,126,181],"trained":[31],"experts":[32],"perform":[34],"labor-intensive":[36],"manual":[37,49,79,182],"analysis":[38],"the":[40,54,61,111,118,160,179],"text.":[41],"The":[42,120,171],"time":[43],"resources":[45],"needed":[46],"conduct":[48],"extraction,":[50],"however,":[51],"has":[52],"limited":[53],"size":[55],"case":[57],"studies":[58,142],"thus":[60],"generalizability":[62],"results.":[64],"begin":[66],"address":[68],"this":[69],"issue,":[70],"we":[71,93],"conducted":[72],"three":[73,165],"experiments":[74],"evaluate":[76],"crowdsourcing":[77],"requirements":[80,115,132,155],"extraction":[81,116,183,189],"task":[82,121,151,161],"larger":[85],"untrained":[88],"workers.":[89],"In":[90],"experiments,":[92],"carefully":[94],"balance":[95],"worker":[96,104,169],"payment":[97],"overall":[99],"cost,":[100],"as":[101,103],"well":[102],"training":[105],"data":[107,127],"quality":[108],"study":[110],"feasibility":[112],"distributing":[114],"crowd.":[119],"consists":[122],"descriptions":[125],"collection,":[128],"sharing":[129],"usage":[131],"from":[133,139],"privacy":[134],"policies.":[135],"We":[136],"present":[137],"results":[138],"two":[140],"pilot":[141],"third":[145],"experiment":[146],"justify":[148],"applying":[149],"decomposition":[152,162],"approach":[153],"extraction.":[156],"Our":[157],"contributions":[158],"include":[159],"workflow":[163],"metrics":[166],"measuring":[168],"performance.":[170],"final":[172],"evaluation":[173],"shows":[174],"60%":[176],"reduction":[177],"in":[178,188],"cost":[180],"with":[184],"16%":[186],"increase":[187],"coverage.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-25T21:42:39.735039","created_date":"2025-10-10T00:00:00"}
