{"id":"https://openalex.org/W2788635322","doi":"https://doi.org/10.1145/3178876.3186012","title":"An Attention Factor Graph Model for Tweet Entity Linking","display_name":"An Attention Factor Graph Model for Tweet Entity Linking","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2788635322","doi":"https://doi.org/10.1145/3178876.3186012","mag":"2788635322"},"language":"en","primary_location":{"id":"doi:10.1145/3178876.3186012","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3178876.3186012","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3178876.3186012","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027193119","display_name":"Chenwei Ran","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chenwei Ran","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101956272","display_name":"Wei Shen","orcid":"https://orcid.org/0000-0003-3479-1165"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Shen","raw_affiliation_strings":["Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100630868","display_name":"Jianyong Wang","orcid":"https://orcid.org/0000-0002-7555-170X"},"institutions":[{"id":"https://openalex.org/I118574674","display_name":"Jiangsu Normal University","ror":"https://ror.org/051hvcm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I118574674"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianyong Wang","raw_affiliation_strings":["Tsinghua University & Jiangsu Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University & Jiangsu Normal University, Beijing, China","institution_ids":["https://openalex.org/I99065089","https://openalex.org/I118574674"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027193119"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":2.769,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.92302547,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1135","last_page":"1144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"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":0.9990000128746033,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8586297035217285},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7716420888900757},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.7164011001586914},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5602133870124817},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5412601232528687},{"id":"https://openalex.org/keywords/factor","display_name":"Factor (programming language)","score":0.534455418586731},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.47962531447410583},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.44273295998573303},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4304615557193756},{"id":"https://openalex.org/keywords/entity-linking","display_name":"Entity linking","score":0.4287172853946686},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3793240487575531},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3781641721725464},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34555375576019287},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.20413681864738464},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.12763920426368713}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8586297035217285},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7716420888900757},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.7164011001586914},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5602133870124817},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5412601232528687},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.534455418586731},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.47962531447410583},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.44273295998573303},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4304615557193756},{"id":"https://openalex.org/C96711827","wikidata":"https://www.wikidata.org/wiki/Q17012245","display_name":"Entity linking","level":3,"score":0.4287172853946686},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3793240487575531},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3781641721725464},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34555375576019287},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.20413681864738464},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.12763920426368713},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3178876.3186012","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3178876.3186012","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3178876.3186012","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3178876.3186012","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W11298561","https://openalex.org/W24664060","https://openalex.org/W86887328","https://openalex.org/W1514461580","https://openalex.org/W1548663377","https://openalex.org/W1560512119","https://openalex.org/W1586532344","https://openalex.org/W1960027552","https://openalex.org/W1964189668","https://openalex.org/W1993715838","https://openalex.org/W2004858782","https://openalex.org/W2013579020","https://openalex.org/W2018165284","https://openalex.org/W2046240631","https://openalex.org/W2054745418","https://openalex.org/W2057047055","https://openalex.org/W2083381833","https://openalex.org/W2096744070","https://openalex.org/W2107559689","https://openalex.org/W2119759918","https://openalex.org/W2139694477","https://openalex.org/W2147527908","https://openalex.org/W2187561416","https://openalex.org/W2250387192","https://openalex.org/W2252231772","https://openalex.org/W2252250824","https://openalex.org/W2270414365","https://openalex.org/W2515462165","https://openalex.org/W2575403103","https://openalex.org/W2604444602"],"related_works":["https://openalex.org/W2368605798","https://openalex.org/W2518037665","https://openalex.org/W2348524959","https://openalex.org/W2477036161","https://openalex.org/W2368049389","https://openalex.org/W2384861574","https://openalex.org/W4294565801","https://openalex.org/W2170801710","https://openalex.org/W2952704802","https://openalex.org/W2741781807"],"abstract_inverted_index":{"The":[0,223],"rapid":[1],"expansion":[2],"of":[3,171,192,208,235],"Twitter":[4,18,27,51],"has":[5,150],"attracted":[6],"worldwide":[7],"attention.":[8],"With":[9],"more":[10],"than":[11],"500":[12],"million":[13],"tweets":[14,68],"posted":[15],"per":[16],"day,":[17],"becomes":[19],"an":[20],"invaluable":[21],"information":[22,49,94],"and":[23,39,47,72,95,113,154,238],"knowledge":[24],"source.":[25],"Many":[26,74],"related":[28],"tasks":[29],"have":[30,77],"been":[31,78],"studied,":[32],"such":[33,87],"as":[34,88],"event":[35],"extraction,":[36],"hashtag":[37],"recommendation,":[38],"topic":[40],"detection.":[41],"A":[42],"critical":[43],"step":[44],"in":[45,56,103,156,183,233],"understanding":[46],"mining":[48],"from":[50],"is":[52,63,122],"to":[53,80,115,126,167,197],"disambiguate":[54],"entities":[55,166],"tweets,":[57],"i.e.,":[58],"tweet":[59,83,140,221],"entity":[60,84,141],"linking.":[61],"It":[62],"a":[64,145,189],"challenging":[65],"task":[66],"because":[67],"are":[69,110],"short,":[70],"noisy,":[71],"fresh.":[73],"tweet-specific":[75],"signals":[76],"found":[79],"solve":[81,198],"the":[82,128,139,169,180,184,199,205,209,242],"linking":[85,142],"problem,":[86],"user":[89],"interest,":[90],"temporal":[91],"popularity,":[92],"location":[93],"so":[96],"on.":[97],"However,":[98],"two":[99,217],"common":[100],"weaknesses":[101],"exist":[102],"previous":[104],"work.":[105],"First,":[106],"most":[107],"proposed":[108],"models":[109],"not":[111,123],"flexible":[112],"extendable":[114],"fit":[116],"new":[117,190],"signals.":[118],"Second,":[119],"their":[120],"scalability":[121,170],"good":[124],"enough":[125],"handle":[127],"large-scale":[129],"social":[130],"network":[131],"like":[132],"Twitter.":[133],"In":[134],"this":[135],"work,":[136],"we":[137,187],"formalize":[138],"problem":[143,202],"into":[144],"factor":[146,185,210],"graph":[147],"model":[148,215,229],"which":[149,174],"shown":[151],"its":[152],"effectiveness":[153,237],"efficiency":[155,239],"many":[157],"other":[158],"applications.":[159],"We":[160,212],"also":[161],"propose":[162,188],"selective":[163],"attention":[164,181,201],"over":[165],"increase":[168],"our":[172,214,228],"model,":[173],"brings":[175],"linear":[176],"complexity.":[177],"To":[178],"adopt":[179],"mechanism":[182],"graph,":[186],"type":[191],"nodes":[193,196],"called":[194],"pseudo-variable":[195],"asymmetry":[200],"caused":[203],"by":[204],"undirected":[206],"characteristic":[207],"graph.":[211],"evaluated":[213],"on":[216],"different":[218],"manually":[219],"annotated":[220],"datasets.":[222],"experimental":[224],"results":[225],"show":[226],"that":[227],"achieves":[230],"better":[231],"performance":[232],"terms":[234],"both":[236],"compared":[240],"with":[241],"state-of-the-art":[243],"approaches.":[244]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}