{"id":"https://openalex.org/W4391096329","doi":"https://doi.org/10.1109/bigdata59044.2023.10386192","title":"Anaphoric Ambiguity Resolution in Software Requirement Texts","display_name":"Anaphoric Ambiguity Resolution in Software Requirement Texts","publication_year":2023,"publication_date":"2023-12-15","ids":{"openalex":"https://openalex.org/W4391096329","doi":"https://doi.org/10.1109/bigdata59044.2023.10386192"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata59044.2023.10386192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata59044.2023.10386192","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5015876015","display_name":"Sanaz Mohammad Jafari","orcid":null},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sanaz Mohammad Jafari","raw_affiliation_strings":["Toronto Metropolitan University,Data Science Lab,Toronto,Canada","Data Science Lab, Toronto Metropolitan University, Toronto, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toronto Metropolitan University,Data Science Lab,Toronto,Canada","institution_ids":["https://openalex.org/I530967"]},{"raw_affiliation_string":"Data Science Lab, Toronto Metropolitan University, Toronto, Canada","institution_ids":["https://openalex.org/I530967"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015457657","display_name":"Sava\u015f Y\u0131ld\u0131r\u0131m","orcid":"https://orcid.org/0000-0002-7764-2891"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Savas Yildirim","raw_affiliation_strings":["Toronto Metropolitan University,Data Science Lab,Toronto,Canada","Data Science Lab, Toronto Metropolitan University, Toronto, Canada","Istanbul Bilgi University, Toronto, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toronto Metropolitan University,Data Science Lab,Toronto,Canada","institution_ids":["https://openalex.org/I530967"]},{"raw_affiliation_string":"Data Science Lab, Toronto Metropolitan University, Toronto, Canada","institution_ids":["https://openalex.org/I530967"]},{"raw_affiliation_string":"Istanbul Bilgi University, Toronto, Canada","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070091996","display_name":"M\u00fccahit \u00c7evik","orcid":"https://orcid.org/0000-0003-4020-6305"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mucahit Cevik","raw_affiliation_strings":["Toronto Metropolitan University,Data Science Lab,Toronto,Canada","Data Science Lab, Toronto Metropolitan University, Toronto, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toronto Metropolitan University,Data Science Lab,Toronto,Canada","institution_ids":["https://openalex.org/I530967"]},{"raw_affiliation_string":"Data Science Lab, Toronto Metropolitan University, Toronto, Canada","institution_ids":["https://openalex.org/I530967"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ayse Basar","orcid":null},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ayse Basar","raw_affiliation_strings":["Toronto Metropolitan University,Data Science Lab,Toronto,Canada","Data Science Lab, Toronto Metropolitan University, Toronto, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toronto Metropolitan University,Data Science Lab,Toronto,Canada","institution_ids":["https://openalex.org/I530967"]},{"raw_affiliation_string":"Data Science Lab, Toronto Metropolitan University, Toronto, Canada","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I530967"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4722","last_page":"4730"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9998999834060669,"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":0.9998999834060669,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9966999888420105,"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/T10430","display_name":"Software Engineering Techniques and Practices","score":0.9962999820709229,"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/ambiguity","display_name":"Ambiguity","score":0.8467433452606201},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7936525344848633},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.48467734456062317},{"id":"https://openalex.org/keywords/requirements-engineering","display_name":"Requirements engineering","score":0.4734637141227722},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.45823007822036743},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4514046907424927},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.41334858536720276},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4111464321613312},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.38240426778793335},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.3782123625278473},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13300108909606934},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.11686572432518005}],"concepts":[{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.8467433452606201},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7936525344848633},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.48467734456062317},{"id":"https://openalex.org/C6604083","wikidata":"https://www.wikidata.org/wiki/Q376937","display_name":"Requirements engineering","level":3,"score":0.4734637141227722},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.45823007822036743},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4514046907424927},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.41334858536720276},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4111464321613312},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38240426778793335},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.3782123625278473},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13300108909606934},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.11686572432518005},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","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":1,"locations":[{"id":"doi:10.1109/bigdata59044.2023.10386192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata59044.2023.10386192","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2005732451","https://openalex.org/W2048279992","https://openalex.org/W2807026730","https://openalex.org/W2896457183","https://openalex.org/W2920114910","https://openalex.org/W2963748441","https://openalex.org/W2965373594","https://openalex.org/W2978017171","https://openalex.org/W3001279689","https://openalex.org/W3003276437","https://openalex.org/W3011411500","https://openalex.org/W3034797437","https://openalex.org/W3034928924","https://openalex.org/W3163827648","https://openalex.org/W3168867926","https://openalex.org/W3185341429","https://openalex.org/W3211686893","https://openalex.org/W4284689801","https://openalex.org/W4288089799","https://openalex.org/W4292779060","https://openalex.org/W4309674289","https://openalex.org/W4385245566","https://openalex.org/W6691479500","https://openalex.org/W6739901393","https://openalex.org/W6755207826","https://openalex.org/W6766673545","https://openalex.org/W6768851824","https://openalex.org/W6769627184","https://openalex.org/W6772383348","https://openalex.org/W6778883912","https://openalex.org/W6796581206"],"related_works":["https://openalex.org/W2353179089","https://openalex.org/W2923538289","https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2353125546","https://openalex.org/W2352448290","https://openalex.org/W2470643824","https://openalex.org/W2380820513","https://openalex.org/W4400595174","https://openalex.org/W2913146933"],"abstract_inverted_index":{"In":[0],"requirements":[1,22,119],"engineering":[2],"(RE),":[3],"anaphoric":[4,67],"ambiguity":[5,68,141],"is":[6],"a":[7,15,28],"frequent":[8],"cause":[9],"of":[10,21,27,32,46,92],"misunderstandings.":[11],"It":[12],"can":[13,79,159],"have":[14,41],"detrimental":[16],"effect":[17],"on":[18,73,116],"the":[19,25,33,49,90],"quality":[20],"and":[23,76,99,121],"jeopardize":[24],"success":[26],"project.":[29],"If":[30],"stakeholders":[31],"system,":[34],"such":[35],"as":[36,142,144],"testers,":[37],"developers,":[38],"or":[39,44],"customers,":[40],"different":[42],"understandings":[43],"interpretations":[45],"software":[47],"requirements,":[48],"system":[50],"may":[51],"not":[52],"be":[53,80],"accepted":[54],"during":[55],"customer":[56],"validation.":[57],"Despite":[58],"its":[59],"significance,":[60],"there":[61],"has":[62],"been":[63],"limited":[64],"investigation":[65],"into":[66],"in":[69,139,147],"RE.":[70],"However,":[71],"focusing":[72],"both":[74],"recognizing":[75],"solving":[77],"uncertainty":[78],"more":[81],"advantageous":[82],"than":[83],"just":[84],"identifying":[85],"it.":[86],"Therefore":[87],"we":[88],"investigated":[89],"effectiveness":[91],"various":[93,113],"QA":[94,130],"learning":[95],"techniques":[96],"including":[97],"encoder-based":[98],"text":[100],"generation-based":[101],"NLP":[102],"models":[103,115,138],"for":[104],"two":[105,117],"goals.":[106],"We":[107,153],"conduct":[108],"detailed":[109],"numerical":[110],"experiments":[111],"using":[112],"transformer":[114],"public":[118],"datasets":[120],"one":[122],"generic":[123],"dataset.":[124],"Our":[125],"results":[126],"indicated":[127],"that":[128,155],"our":[129,156],"architecture":[131,158],"exhibits":[132],"superior":[133],"performance":[134],"compared":[135],"to":[136,149,164],"baseline":[137,151],"detecting":[140],"well":[143],"resolving":[145],"anaphora":[146],"contrast":[148],"other":[150],"approaches.":[152],"showed":[154],"developed":[157],"automatically":[160],"support":[161],"requirement":[162],"development":[163],"minimize":[165],"interpretation":[166],"risk":[167],"between":[168],"stakeholders.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-27T08:26:11.824852","created_date":"2025-10-10T00:00:00"}
