{"id":"https://openalex.org/W2767951967","doi":"https://doi.org/10.1145/3132847.3132856","title":"Deep Context Modeling for Web Query Entity Disambiguation","display_name":"Deep Context Modeling for Web Query Entity Disambiguation","publication_year":2017,"publication_date":"2017-11-06","ids":{"openalex":"https://openalex.org/W2767951967","doi":"https://doi.org/10.1145/3132847.3132856","mag":"2767951967"},"language":"en","primary_location":{"id":"doi:10.1145/3132847.3132856","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3132847.3132856","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 ACM on Conference on Information and Knowledge Management","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/A5055903716","display_name":"Zhen Liao","orcid":"https://orcid.org/0009-0001-0405-0975"},"institutions":[{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]},{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhen Liao","raw_affiliation_strings":["Facebook, Menlo Park, CA, USA"],"affiliations":[{"raw_affiliation_string":"Facebook, Menlo Park, CA, USA","institution_ids":["https://openalex.org/I4210114444","https://openalex.org/I4210099336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102246878","display_name":"Xinying Song","orcid":"https://orcid.org/0009-0002-9445-0717"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinying Song","raw_affiliation_strings":["Microsoft Research, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101180037","display_name":"Yelong Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yelong Shen","raw_affiliation_strings":["Microsoft Research, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050271629","display_name":"Saekoo Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saekoo Lee","raw_affiliation_strings":["Google, Mountain View, CA, USA"],"affiliations":[{"raw_affiliation_string":"Google, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114910293","display_name":"Jianfeng Gao","orcid":"https://orcid.org/0000-0002-5702-6143"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianfeng Gao","raw_affiliation_strings":["Microsoft Research, Redmond, CA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, CA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060322416","display_name":"Ciya Liao","orcid":"https://orcid.org/0000-0001-6788-139X"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ciya Liao","raw_affiliation_strings":["Microsoft Research, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5055903716"],"corresponding_institution_ids":["https://openalex.org/I4210099336","https://openalex.org/I4210114444"],"apc_list":null,"apc_paid":null,"fwci":0.9751,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.82582755,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1757","last_page":"1765"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9995999932289124,"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/T11719","display_name":"Data Quality and Management","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9970999956130981,"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":0.8928492069244385},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5787355899810791},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.566979706287384},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5626416802406311},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5547048449516296},{"id":"https://openalex.org/keywords/entity-linking","display_name":"Entity linking","score":0.49599489569664},{"id":"https://openalex.org/keywords/query-expansion","display_name":"Query expansion","score":0.4937227666378021},{"id":"https://openalex.org/keywords/web-query-classification","display_name":"Web query classification","score":0.44949057698249817},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.43374091386795044},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.39526045322418213},{"id":"https://openalex.org/keywords/web-search-query","display_name":"Web search query","score":0.3787074685096741},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.15827736258506775}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8928492069244385},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5787355899810791},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.566979706287384},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5626416802406311},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5547048449516296},{"id":"https://openalex.org/C96711827","wikidata":"https://www.wikidata.org/wiki/Q17012245","display_name":"Entity linking","level":3,"score":0.49599489569664},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.4937227666378021},{"id":"https://openalex.org/C118689300","wikidata":"https://www.wikidata.org/wiki/Q7978614","display_name":"Web query classification","level":4,"score":0.44949057698249817},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.43374091386795044},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.39526045322418213},{"id":"https://openalex.org/C164120249","wikidata":"https://www.wikidata.org/wiki/Q995982","display_name":"Web search query","level":3,"score":0.3787074685096741},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.15827736258506775},{"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},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3132847.3132856","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3132847.3132856","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 ACM on Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W86887328","https://openalex.org/W1548663377","https://openalex.org/W1678356000","https://openalex.org/W1881631818","https://openalex.org/W1964189668","https://openalex.org/W1988157164","https://openalex.org/W2033478896","https://openalex.org/W2040916592","https://openalex.org/W2064675550","https://openalex.org/W2089524421","https://openalex.org/W2098326081","https://openalex.org/W2098700435","https://openalex.org/W2100341149","https://openalex.org/W2120779048","https://openalex.org/W2127289991","https://openalex.org/W2130495108","https://openalex.org/W2131876387","https://openalex.org/W2136189984","https://openalex.org/W2142920810","https://openalex.org/W2157094299","https://openalex.org/W2250539671","https://openalex.org/W2251008987","https://openalex.org/W2251559320","https://openalex.org/W2252052301","https://openalex.org/W2252231772","https://openalex.org/W2296283641","https://openalex.org/W2296382382","https://openalex.org/W2396582863","https://openalex.org/W2950133940","https://openalex.org/W2963184844","https://openalex.org/W3122775348"],"related_works":["https://openalex.org/W2096359267","https://openalex.org/W2901901036","https://openalex.org/W2026738364","https://openalex.org/W1521725692","https://openalex.org/W2093300859","https://openalex.org/W3008917487","https://openalex.org/W2124814993","https://openalex.org/W2013069866","https://openalex.org/W2113390685","https://openalex.org/W2049540727"],"abstract_inverted_index":{"In":[0,56],"this":[1,57],"paper,":[2,58],"we":[3,59,70,120,144],"presented":[4],"a":[5,24,31,102,110,146,157,171],"new":[6],"study":[7],"for":[8,79,139],"Web":[9,123],"query":[10,111],"entity":[11,53,116],"disambiguation":[12,54],"(QED),":[13],"which":[14,164],"is":[15,34,49,117,179],"the":[16,65,72,81,107,122,140,168,182],"task":[17],"of":[18,67,74,127,134,160,170,176],"disambiguating":[19],"different":[20],"candidate":[21,95],"entities":[22,97],"in":[23,30,86,101,181],"knowledge":[25],"base":[26],"given":[27],"their":[28,94],"mentions":[29],"query.":[32],"QED":[33],"particularly":[35],"challenging":[36],"because":[37],"queries":[38,92,128],"are":[39],"often":[40],"too":[41],"short":[42],"to":[43,63,98,129,150],"provide":[44],"rich":[45],"contextual":[46],"information":[47,85,126],"that":[48],"required":[50],"by":[51],"traditional":[52],"methods.":[55],"propose":[60,145],"several":[61],"methods":[62],"tackle":[64],"problem":[66],"QED.":[68],"First,":[69],"explore":[71],"use":[73],"deep":[75],"neural":[76],"network":[77],"(DNN)":[78],"capturing":[80],"character":[82],"level":[83],"textual":[84],"queries.":[87],"Our":[88],"DNN":[89,141,172],"approach":[90,178],"maps":[91],"and":[93,112],"reference":[96,115],"feature":[99],"vectors":[100],"latent":[103],"semantic":[104],"space":[105],"where":[106],"distance":[108],"between":[109],"its":[113],"correct":[114],"minimized.":[118],"Second,":[119],"utilize":[121],"search":[124],"result":[125],"help":[130],"generate":[131],"large":[132],"amounts":[133],"weakly":[135,153],"supervised":[136,154],"training":[137,148],"data":[138,155],"model.":[142,173],"Third,":[143],"two-stage":[147],"method":[149],"combine":[151],"large-scale":[152,185],"with":[156],"small":[158],"amount":[159],"human":[161],"labeled":[162],"data,":[163],"can":[165],"significantly":[166],"boost":[167],"performance":[169],"The":[174],"effectiveness":[175],"our":[177],"demonstrated":[180],"experiments":[183],"using":[184],"real-world":[186],"datasets.":[187]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
