{"id":"https://openalex.org/W2799154098","doi":"https://doi.org/10.1145/3183713.3183732","title":"Subjective Knowledge Base Construction Powered By Crowdsourcing and Knowledge Base","display_name":"Subjective Knowledge Base Construction Powered By Crowdsourcing and Knowledge Base","publication_year":2018,"publication_date":"2018-05-25","ids":{"openalex":"https://openalex.org/W2799154098","doi":"https://doi.org/10.1145/3183713.3183732","mag":"2799154098"},"language":"en","primary_location":{"id":"doi:10.1145/3183713.3183732","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3183713.3183732","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 International Conference on Management of Data","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/A5035412970","display_name":"Hao Xin","orcid":null},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Hao Xin","raw_affiliation_strings":["Hong Kong University of Science and Technology, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong University of Science and Technology, Hong Kong, China","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017371410","display_name":"Rui Meng","orcid":"https://orcid.org/0000-0001-5902-1787"},"institutions":[{"id":"https://openalex.org/I12615008","display_name":"Beijing Normal-Hong Kong Baptist University","ror":"https://ror.org/04snvc712","country_code":"CN","type":"education","lineage":["https://openalex.org/I12615008"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Meng","raw_affiliation_strings":["BNU-HKBU United International College, Zhuhai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BNU-HKBU United International College, Zhuhai, China","institution_ids":["https://openalex.org/I12615008"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013220122","display_name":"Lei Chen","orcid":"https://orcid.org/0000-0001-8599-4865"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["Hong Kong University of Science and Technology, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong University of Science and Technology, Hong Kong, China","institution_ids":["https://openalex.org/I200769079"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.9743,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.91675682,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1349","last_page":"1361"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9998000264167786,"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":0.9998000264167786,"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/T10028","display_name":"Topic Modeling","score":0.9980999827384949,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9955000281333923,"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":0.7517081499099731},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.7014439105987549},{"id":"https://openalex.org/keywords/crowdsourcing","display_name":"Crowdsourcing","score":0.6572009921073914},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.6101506352424622},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5043798685073853},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.46054714918136597},{"id":"https://openalex.org/keywords/commonsense-knowledge","display_name":"Commonsense knowledge","score":0.4387328326702118},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.4165743589401245},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39111292362213135},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3347797095775604},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.258764386177063}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7517081499099731},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.7014439105987549},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.6572009921073914},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6101506352424622},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5043798685073853},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.46054714918136597},{"id":"https://openalex.org/C30542707","wikidata":"https://www.wikidata.org/wiki/Q1603203","display_name":"Commonsense knowledge","level":3,"score":0.4387328326702118},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.4165743589401245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39111292362213135},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3347797095775604},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.258764386177063}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3183713.3183732","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3183713.3183732","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 International Conference on Management of Data","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":35,"referenced_works":["https://openalex.org/W790941020","https://openalex.org/W1552847225","https://openalex.org/W1573900212","https://openalex.org/W1879495188","https://openalex.org/W1992479406","https://openalex.org/W1993685897","https://openalex.org/W2000519162","https://openalex.org/W2012668444","https://openalex.org/W2016089260","https://openalex.org/W2016753842","https://openalex.org/W2035274534","https://openalex.org/W2056748234","https://openalex.org/W2073068515","https://openalex.org/W2081580037","https://openalex.org/W2094728533","https://openalex.org/W2101349222","https://openalex.org/W2106675345","https://openalex.org/W2115461474","https://openalex.org/W2120396827","https://openalex.org/W2121431555","https://openalex.org/W2122865749","https://openalex.org/W2123885506","https://openalex.org/W2134677057","https://openalex.org/W2138605095","https://openalex.org/W2183907052","https://openalex.org/W2243633279","https://openalex.org/W2243869100","https://openalex.org/W2337282450","https://openalex.org/W2428834396","https://openalex.org/W2430704425","https://openalex.org/W2535231809","https://openalex.org/W2577737453","https://openalex.org/W2785650693","https://openalex.org/W2792460139","https://openalex.org/W2962795549"],"related_works":["https://openalex.org/W3032998312","https://openalex.org/W1503094549","https://openalex.org/W4384486036","https://openalex.org/W135177976","https://openalex.org/W1979978247","https://openalex.org/W2382915105","https://openalex.org/W1520100787","https://openalex.org/W2620787630","https://openalex.org/W1533009136","https://openalex.org/W2159419920"],"abstract_inverted_index":{"Knowledge":[0,30],"base":[1,111],"construction":[2,112,132,139,237,244],"(KBC)":[3],"has":[4,73,79,160],"become":[5],"a":[6,105,126,149,209,231,258],"hot":[7],"and":[8,32,52,121,140,214,224,245,257,278],"in-time":[9],"topic":[10],"recently":[11],"with":[12,171],"the":[13,28,43,47,59,63,85,116,119,167,179,185,189,195,201,262],"increasing":[14],"application":[15],"need":[16],"of":[17,46,115,135,188,203,240],"large-scale":[18],"knowledge":[19,78,110,117,247,255,273],"bases":[20,256],"(KBs),":[21],"such":[22],"as":[23,58,208],"semantic":[24],"search,":[25],"QA":[26,35],"systems,":[27],"Google":[29],"Graph":[31],"IBM":[33],"Watson":[34],"System.":[36],"Existing":[37],"KBs":[38,277],"mainly":[39],"focus":[40],"on":[41,88,253],"encoding":[42],"factual":[44],"facts":[45,274],"world,":[48],"e.g.,":[49],"city":[50],"area":[51],"company":[53],"product,":[54],"which":[55,66,92,133,178,238],"are":[56],"regarded":[57],"objective":[60,162],"knowledge,":[61,65],"whereas":[62],"subjective":[64,77,109,130,137,141,151,169,186,204,235,242,246,272],"is":[67,181],"frequently":[68],"mentioned":[69],"in":[70,177],"Web":[71],"queries,":[72],"been":[74],"neglected.":[75],"The":[76],"no":[80],"documented":[81],"ground":[82],"truth,":[83],"instead,":[84],"truth":[86],"relies":[87],"people's":[89],"dominant":[90],"opinion,":[91],"can":[93,268],"be":[94],"solicited":[95],"from":[96,118,154,174,275],"online":[97],"crowd":[98,120,180,196],"workers.":[99],"In":[100,191],"our":[101,251,282],"work,":[102],"we":[103,145,165,199,267],"propose":[104,215],"KBC":[106],"framework":[107,128,252],"for":[108,129,234],"taking":[113],"advantage":[114],"existing":[122,155,175,276],"KBs.":[123],"We":[124,229,249],"develop":[125,230],"two-staged":[127],"KB":[131,138,142,152,170,205,236,243],"consists":[134,239],"core":[136,150,168,241],"enrichment.":[143,248],"Firstly,":[144],"try":[146],"to":[147,183,193],"build":[148],"mined":[153],"KBs,":[156,176],"where":[157],"every":[158],"instance":[159,211,217,222,226],"rich":[161],"properties.":[163],"Then,":[164],"populate":[166],"instances":[172],"extracted":[173],"leverage":[182],"annotate":[184],"property":[187],"instances.":[190],"order":[192],"optimize":[194],"annotation":[197,212,218,223,227],"process,":[198],"formulate":[200],"problem":[202,213],"enrichment":[206],"procedure":[207],"cost-aware":[210],"two":[216],"algorithms,":[219],"i.e.,":[220],"adaptive":[221],"batch-mode":[225],"algorithms.":[228],"two-stage":[232],"system":[233],"evaluate":[250],"real":[254,259],"crowdsourcing":[260,279],"platform,":[261],"experimental":[263],"results":[264],"show":[265],"that":[266],"derive":[269],"high":[270],"quality":[271],"techniques":[280],"through":[281],"proposed":[283],"framework.":[284]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
