{"id":"https://openalex.org/W2963662719","doi":"https://doi.org/10.1109/icdm.2016.0060","title":"Modeling Ambiguity, Subjectivity, and Diverging Viewpoints in Opinion Question Answering Systems","display_name":"Modeling Ambiguity, Subjectivity, and Diverging Viewpoints in Opinion Question Answering Systems","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2963662719","doi":"https://doi.org/10.1109/icdm.2016.0060","mag":"2963662719"},"language":"en","primary_location":{"id":"doi:10.1109/icdm.2016.0060","doi":"https://doi.org/10.1109/icdm.2016.0060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2016.0060","pdf_url":null,"source":{"id":"https://openalex.org/S4210214883","display_name":"Proceedings","issn_l":"1550-4786","issn":["1550-4786","2374-8486"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 16th International Conference on Data Mining (ICDM)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1610.08095","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046172814","display_name":"Mengting Wan","orcid":"https://orcid.org/0000-0002-5298-1221","observed_orcids":["https://orcid.org/0000-0002-5298-1221"]},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mengting Wan","raw_affiliation_strings":["University of California, San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021827617","display_name":"Julian McAuley","orcid":"https://orcid.org/0000-0003-0955-7588","observed_orcids":["https://orcid.org/0000-0003-0955-7588"]},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Julian McAuley","raw_affiliation_strings":["University of California, San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, San Diego","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I36258959"],"apc_list":null,"apc_paid":null,"fwci":7.7045,"has_fulltext":true,"cited_by_count":92,"citation_normalized_percentile":{"value":0.98303014,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":100},"biblio":{"volume":"2016","issue":null,"first_page":"489","last_page":"498"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13274","display_name":"Expert finding and Q&A systems","score":0.6064000129699707,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.6064000129699707,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.29980000853538513,"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/T10028","display_name":"Topic Modeling","score":0.06480000168085098,"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/product-reviews","display_name":"product reviews","score":0.9419999718666077},{"id":"https://openalex.org/keywords/ambiguity","display_name":"ambiguity","score":0.5400000214576721},{"id":"https://openalex.org/keywords/subjectivity","display_name":"subjectivity","score":0.9300000071525574},{"id":"https://openalex.org/keywords/personalization","display_name":"personalization","score":0.9110000133514404},{"id":"https://openalex.org/keywords/question-answering-dataset","display_name":"question answering dataset","score":0.7549999952316284}],"concepts":[{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.7874699831008911},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.786561131477356},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7611790895462036},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.7515231370925903},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.7316523790359497},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.5946528911590576},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5825478434562683},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.5698802471160889},{"id":"https://openalex.org/C202889954","wikidata":"https://www.wikidata.org/wiki/Q1139554","display_name":"Subjectivity","level":2,"score":0.5110967755317688},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.4843836724758148},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.44686853885650635},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4097691774368286},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.40492838621139526},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.37393274903297424},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.2848498821258545},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2647784948348999},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.10200586915016174},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icdm.2016.0060","doi":"https://doi.org/10.1109/icdm.2016.0060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2016.0060","pdf_url":null,"source":{"id":"https://openalex.org/S4210214883","display_name":"Proceedings","issn_l":"1550-4786","issn":["1550-4786","2374-8486"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 16th International Conference on Data Mining (ICDM)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1610.08095","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1610.08095","pdf_url":"https://arxiv.org/pdf/1610.08095","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.1610.08095","doi":"https://doi.org/10.48550/arxiv.1610.08095","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1610.08095","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},{"id":"mag:2745449806","doi":null,"is_oa":false,"landing_page_url":"http://jglobal.jst.go.jp/en/public/20090422/201702254058009996","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1610.08095","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1610.08095","pdf_url":"https://arxiv.org/pdf/1610.08095","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G3365216859","display_name":"BD Spokes: SPOKE: WEST: Collaborative: MetroInsight: Knowledge Discovery and Real-Time Interventions from Sensory Data Flows in Urban Spaces","funder_award_id":"1636879","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963662719.pdf","grobid_xml":"https://content.openalex.org/works/W2963662719.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1532325895","https://openalex.org/W1585953746","https://openalex.org/W1993077754","https://openalex.org/W1999180776","https://openalex.org/W2025653905","https://openalex.org/W2049633694","https://openalex.org/W2061873838","https://openalex.org/W2080558111","https://openalex.org/W2096259080","https://openalex.org/W2098717097","https://openalex.org/W2101306587","https://openalex.org/W2123249581","https://openalex.org/W2123442489","https://openalex.org/W2134305421","https://openalex.org/W2144091323","https://openalex.org/W2153252192","https://openalex.org/W2154652894","https://openalex.org/W2160409620","https://openalex.org/W2160660844","https://openalex.org/W2162885287","https://openalex.org/W2243869100","https://openalex.org/W2397663929","https://openalex.org/W2892011343","https://openalex.org/W3029645440","https://openalex.org/W4213009331","https://openalex.org/W4301909677"],"related_works":["https://openalex.org/W1993077754","https://openalex.org/W3094171871","https://openalex.org/W4382201609","https://openalex.org/W2965826089","https://openalex.org/W3023687419","https://openalex.org/W1999180776","https://openalex.org/W7160711888","https://openalex.org/W2133670637","https://openalex.org/W2904258646","https://openalex.org/W1513194152"],"abstract_inverted_index":{"Product":[0],"review":[1,49],"websites":[2,50],"provide":[3],"an":[4],"incredible":[5],"lens":[6],"into":[7],"the":[8,58,116,155,166,169,180,222],"wide":[9],"variety":[10],"of":[11,15,118,147,221,224],"opinions":[12,71],"and":[13,18,33,85,143,157,168,171,207],"experiences":[14],"different":[16,74,96],"people,":[17],"play":[19],"a":[20,61,106,161,189,217],"critical":[21],"role":[22],"in":[23,133,177],"helping":[24],"users":[25,53],"discover":[26],"products":[27],"that":[28,39,89,105,130,202],"match":[29],"their":[30],"personal":[31],"needs":[32],"preferences.":[34],"To":[35],"help":[36],"address":[37],"questions":[38,56,79,92],"can't":[40],"easily":[41],"be":[42,82,151,175,183],"answered":[43],"by":[44],"reading":[45],"others'":[46],"reviews,":[47,122],"some":[48],"also":[51,81,216],"allow":[52],"to":[54,57,77,153,182,211],"pose":[55],"community":[59],"via":[60],"question-answering":[62,119],"(QA)":[63],"system.":[64],"As":[65],"one":[66],"would":[67],"expect,":[68],"just":[69],"as":[70],"diverge":[72],"among":[73],"reviewers,":[75],"answers":[76,148],"such":[78,91],"may":[80],"subjective,":[83,227],"opinionated,":[84],"divergent.":[86],"This":[87],"means":[88],"answering":[90],"automatically":[93],"is":[94,103,110],"quite":[95],"from":[97],"traditional":[98],"QA":[99,191],"tasks,":[100],"where":[101],"it":[102,123],"assumed":[104],"single":[107],"'correct'":[108],"answer":[109,163],"available.":[111],"While":[112],"recent":[113],"work":[114],"introduced":[115],"idea":[117],"using":[120],"product":[121],"did":[124],"not":[125],"account":[126],"for":[127,179,205],"two":[128],"aspects":[129],"we":[131,187],"consider":[132],"this":[134,144],"paper:":[135],"(1)":[136],"Questions":[137],"have":[138],"multiple,":[139],"often":[140],"divergent,":[141],"answers,":[142,214],"full":[145],"spectrum":[146],"should":[149,174],"somehow":[150],"used":[152],"train":[154],"system,":[156],"(2)":[158],"What":[159],"makes":[160],"'good'":[162],"depends":[164],"on":[165],"asker":[167],"answerer,":[170],"these":[172],"factors":[173],"incorporated":[176],"order":[178],"system":[181],"more":[184,218],"personalized.":[185],"Here":[186],"build":[188],"new":[190],"dataset":[192],"with":[193],"800":[194],"thousand":[195],"questions-and":[196],"over":[197],"3.1":[198],"million":[199],"answers-and":[200],"show":[201],"explicitly":[203],"accounting":[204],"personalization":[206],"ambiguity":[208],"leads":[209],"both":[210],"quantitatively":[212],"better":[213],"but":[215,226],"nuanced":[219],"view":[220],"range":[223],"supporting,":[225],"opinions.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":19},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2019-07-30T00:00:00"}