{"id":"https://openalex.org/W2783970129","doi":"https://doi.org/10.1109/bigdata.2017.8258463","title":"An entity disambiguation method based on LeaderRank","display_name":"An entity disambiguation method based on LeaderRank","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2783970129","doi":"https://doi.org/10.1109/bigdata.2017.8258463","mag":"2783970129"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2017.8258463","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258463","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big 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/A5046084292","display_name":"Bingjing Jia","orcid":"https://orcid.org/0000-0002-7555-0723"},"institutions":[{"id":"https://openalex.org/I4210109416","display_name":"Anhui Science and Technology University","ror":"https://ror.org/01pn91c28","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210109416"]},{"id":"https://openalex.org/I184681353","display_name":"Anhui University of Science and Technology","ror":"https://ror.org/00q9atg80","country_code":"CN","type":"education","lineage":["https://openalex.org/I184681353"]},{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bingjing Jia","raw_affiliation_strings":["Anhui Science and Technology University, Bengbu, China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Anhui Science and Technology University, Bengbu, China","institution_ids":["https://openalex.org/I4210109416","https://openalex.org/I184681353"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101432128","display_name":"Bin Wu","orcid":"https://orcid.org/0000-0002-7112-126X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Wu","raw_affiliation_strings":["Beijing Key Laboratory of Intelligence Telecommunication Software and Multime, Beijing, China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Intelligence Telecommunication Software and Multime, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063717062","display_name":"Jinna Lv","orcid":"https://orcid.org/0000-0002-3416-1465"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinna Lv","raw_affiliation_strings":["Beijing Key Laboratory of Intelligence Telecommunication Software and Multime, Beijing, China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Intelligence Telecommunication Software and Multime, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089769808","display_name":"Pengpeng Zhou","orcid":"https://orcid.org/0000-0002-5359-1540"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengpeng Zhou","raw_affiliation_strings":["Beijing Key Laboratory of Intelligence Telecommunication Software and Multime, Beijing, China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Intelligence Telecommunication Software and Multime, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063427032","display_name":"Yao Bu","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Bu","raw_affiliation_strings":["Beijing Key Laboratory of Intelligence Telecommunication Software and Multime, Beijing, China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Intelligence Telecommunication Software and Multime, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009499465","display_name":"Ying Xing","orcid":"https://orcid.org/0000-0003-2807-1911"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Xing","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5046084292"],"corresponding_institution_ids":["https://openalex.org/I139759216","https://openalex.org/I184681353","https://openalex.org/I4210109416"],"apc_list":null,"apc_paid":null,"fwci":0.195,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6484816,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"6","issue":null,"first_page":"4337","last_page":"4342"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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/T11719","display_name":"Data Quality and Management","score":0.9990000128746033,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.998199999332428,"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/computer-science","display_name":"Computer science","score":0.8374444246292114},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6808222532272339},{"id":"https://openalex.org/keywords/entity-linking","display_name":"Entity linking","score":0.6738021373748779},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5101792812347412},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.5027227401733398},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.49887919425964355},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4985361099243164},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.48931142687797546},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.47857263684272766},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.47674262523651123},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46054357290267944},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4539468288421631},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4389874041080475},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.4166862964630127},{"id":"https://openalex.org/keywords/link-analysis","display_name":"Link analysis","score":0.4142778515815735},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4141431748867035},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1006132960319519}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8374444246292114},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6808222532272339},{"id":"https://openalex.org/C96711827","wikidata":"https://www.wikidata.org/wiki/Q17012245","display_name":"Entity linking","level":3,"score":0.6738021373748779},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5101792812347412},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.5027227401733398},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.49887919425964355},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4985361099243164},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.48931142687797546},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.47857263684272766},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.47674262523651123},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46054357290267944},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4539468288421631},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4389874041080475},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.4166862964630127},{"id":"https://openalex.org/C1173588","wikidata":"https://www.wikidata.org/wiki/Q6554294","display_name":"Link analysis","level":2,"score":0.4142778515815735},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4141431748867035},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1006132960319519},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2017.8258463","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258463","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","score":0.7599999904632568,"display_name":"No poverty"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W11298561","https://openalex.org/W86887328","https://openalex.org/W1632875369","https://openalex.org/W1964189668","https://openalex.org/W1971941321","https://openalex.org/W1985451470","https://openalex.org/W2040916592","https://openalex.org/W2085337304","https://openalex.org/W2100341149","https://openalex.org/W2119737821","https://openalex.org/W2151048449","https://openalex.org/W2252052301","https://openalex.org/W2295227292","https://openalex.org/W2367004377","https://openalex.org/W2466190630","https://openalex.org/W3003765025","https://openalex.org/W6603544577","https://openalex.org/W6636650920","https://openalex.org/W6682141183","https://openalex.org/W6691480130"],"related_works":["https://openalex.org/W1541691357","https://openalex.org/W2090135255","https://openalex.org/W2168409722","https://openalex.org/W4387163706","https://openalex.org/W2026505290","https://openalex.org/W2782437235","https://openalex.org/W1993715838","https://openalex.org/W2359088421","https://openalex.org/W2181629536","https://openalex.org/W2119465010"],"abstract_inverted_index":{"Entity":[0],"Disambiguation":[1],"is":[2,14,148],"commonly":[3],"faced":[4],"in":[5,38,88],"semantic":[6],"search":[7],"and":[8,42,68,101,132],"knowledge":[9],"base":[10],"population.":[11],"However,":[12],"it":[13],"a":[15,39,81],"challenging":[16],"task":[17],"because":[18],"of":[19,22],"the":[20,46,66,69,110,118],"diversity":[21],"mentions.":[23,136],"Previous":[24],"methods":[25,147],"can":[26],"be":[27],"classified":[28],"into":[29,57],"two":[30,142],"main":[31],"groups.":[32],"One":[33],"focuses":[34],"on":[35,45,109,141],"disambiguating":[36],"mentions":[37,54,87],"document":[40,133],"independently":[41],"mainly":[43],"relies":[44],"local":[47],"context":[48,67],"similarity.":[49],"The":[50],"other":[51],"collectively":[52,85],"disambiguates":[53],"only":[55],"taking":[56],"account":[58],"link":[59,70,119],"information.":[60],"These":[61],"are":[62,72],"not":[63],"appropriate":[64],"when":[65],"information":[71,120],"poor":[73],"or":[74],"misleading.":[75],"In":[76],"this":[77],"paper,":[78],"we":[79,105,124],"propose":[80],"new":[82],"method":[83],"to":[84,113,117,134],"disambiguate":[86,135],"documents.":[89],"Our":[90,137],"proposed":[91],"framework":[92],"considers":[93],"three":[94],"features,":[95],"including":[96],"text":[97,128],"similarity,":[98],"entity":[99,102,131],"popularity,":[100],"relationship.":[103],"First":[104],"adopt":[106],"LeaderRank":[107],"algorithm":[108],"graph":[111],"model":[112],"rank":[114],"entities":[115],"according":[116],"among":[121],"entities.":[122],"Then":[123],"combine":[125],"with":[126],"global":[127],"similarity":[129],"between":[130],"detailed":[138],"experimental":[139],"evaluation":[140],"benchmark":[143],"datasets":[144],"demonstrates":[145],"our":[146],"effective.":[149]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
