{"id":"https://openalex.org/W2963186170","doi":"https://doi.org/10.18653/v1/d16-1063","title":"WordRank: Learning Word Embeddings via Robust Ranking","display_name":"WordRank: Learning Word Embeddings via Robust Ranking","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2963186170","doi":"https://doi.org/10.18653/v1/d16-1063","mag":"2963186170"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d16-1063","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d16-1063","pdf_url":"https://www.aclweb.org/anthology/D16-1063.pdf","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 2016 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D16-1063.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036338045","display_name":"Shihao Ji","orcid":"https://orcid.org/0000-0002-3573-5379"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]},{"id":"https://openalex.org/I4210158342","display_name":"Intel (United Kingdom)","ror":"https://ror.org/058cxws58","country_code":"GB","type":"company","lineage":["https://openalex.org/I1343180700","https://openalex.org/I4210158342"]},{"id":"https://openalex.org/I185103710","display_name":"University of California, Santa Cruz","ror":"https://ror.org/03s65by71","country_code":"US","type":"education","lineage":["https://openalex.org/I185103710"]}],"countries":["GB","JP","US"],"is_corresponding":true,"raw_author_name":"Shihao Ji","raw_affiliation_strings":["Parallel Computing Lab, Intel","University of Tokyo","Purdue University","Univ. of California, Santa Cruz"],"affiliations":[{"raw_affiliation_string":"Parallel Computing Lab, Intel","institution_ids":["https://openalex.org/I4210158342"]},{"raw_affiliation_string":"University of Tokyo","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"Univ. of California, Santa Cruz","institution_ids":["https://openalex.org/I185103710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061527181","display_name":"Hyokun Yun","orcid":null},"institutions":[{"id":"https://openalex.org/I4210158342","display_name":"Intel (United Kingdom)","ror":"https://ror.org/058cxws58","country_code":"GB","type":"company","lineage":["https://openalex.org/I1343180700","https://openalex.org/I4210158342"]},{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]},{"id":"https://openalex.org/I185103710","display_name":"University of California, Santa Cruz","ror":"https://ror.org/03s65by71","country_code":"US","type":"education","lineage":["https://openalex.org/I185103710"]}],"countries":["GB","JP","US"],"is_corresponding":false,"raw_author_name":"Hyokun Yun","raw_affiliation_strings":["University of Tokyo","Parallel Computing Lab, Intel","Univ. of California, Santa Cruz","Purdue University"],"affiliations":[{"raw_affiliation_string":"University of Tokyo","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"Parallel Computing Lab, Intel","institution_ids":["https://openalex.org/I4210158342"]},{"raw_affiliation_string":"Univ. of California, Santa Cruz","institution_ids":["https://openalex.org/I185103710"]},{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016498717","display_name":"Pinar Yanardag","orcid":"https://orcid.org/0000-0003-0193-7818"},"institutions":[{"id":"https://openalex.org/I185103710","display_name":"University of California, Santa Cruz","ror":"https://ror.org/03s65by71","country_code":"US","type":"education","lineage":["https://openalex.org/I185103710"]},{"id":"https://openalex.org/I4210158342","display_name":"Intel (United Kingdom)","ror":"https://ror.org/058cxws58","country_code":"GB","type":"company","lineage":["https://openalex.org/I1343180700","https://openalex.org/I4210158342"]},{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["GB","JP","US"],"is_corresponding":false,"raw_author_name":"Pinar Yanardag","raw_affiliation_strings":["Purdue University","Univ. of California, Santa Cruz","Parallel Computing Lab, Intel","University of Tokyo"],"affiliations":[{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"Univ. of California, Santa Cruz","institution_ids":["https://openalex.org/I185103710"]},{"raw_affiliation_string":"Parallel Computing Lab, Intel","institution_ids":["https://openalex.org/I4210158342"]},{"raw_affiliation_string":"University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102724770","display_name":"Shin Matsushima","orcid":"https://orcid.org/0000-0002-8160-4310"},"institutions":[{"id":"https://openalex.org/I185103710","display_name":"University of California, Santa Cruz","ror":"https://ror.org/03s65by71","country_code":"US","type":"education","lineage":["https://openalex.org/I185103710"]},{"id":"https://openalex.org/I4210158342","display_name":"Intel (United Kingdom)","ror":"https://ror.org/058cxws58","country_code":"GB","type":"company","lineage":["https://openalex.org/I1343180700","https://openalex.org/I4210158342"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]},{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["GB","JP","US"],"is_corresponding":false,"raw_author_name":"Shin Matsushima","raw_affiliation_strings":["Purdue University","Univ. of California, Santa Cruz","University of Tokyo","Parallel Computing Lab, Intel"],"affiliations":[{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"Univ. of California, Santa Cruz","institution_ids":["https://openalex.org/I185103710"]},{"raw_affiliation_string":"University of Tokyo","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"Parallel Computing Lab, Intel","institution_ids":["https://openalex.org/I4210158342"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013623933","display_name":"S. V. N. Vishwanathan","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]},{"id":"https://openalex.org/I4210158342","display_name":"Intel (United Kingdom)","ror":"https://ror.org/058cxws58","country_code":"GB","type":"company","lineage":["https://openalex.org/I1343180700","https://openalex.org/I4210158342"]},{"id":"https://openalex.org/I185103710","display_name":"University of California, Santa Cruz","ror":"https://ror.org/03s65by71","country_code":"US","type":"education","lineage":["https://openalex.org/I185103710"]}],"countries":["GB","JP","US"],"is_corresponding":false,"raw_author_name":"S. V. N. Vishwanathan","raw_affiliation_strings":["Parallel Computing Lab, Intel","Purdue University","University of Tokyo","Univ. of California, Santa Cruz"],"affiliations":[{"raw_affiliation_string":"Parallel Computing Lab, Intel","institution_ids":["https://openalex.org/I4210158342"]},{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"University of Tokyo","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"Univ. of California, Santa Cruz","institution_ids":["https://openalex.org/I185103710"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5036338045"],"corresponding_institution_ids":["https://openalex.org/I185103710","https://openalex.org/I219193219","https://openalex.org/I4210158342","https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":8.5695,"has_fulltext":true,"cited_by_count":32,"citation_normalized_percentile":{"value":0.97749389,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"658","last_page":"668"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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/T10181","display_name":"Natural Language Processing Techniques","score":1.0,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9976999759674072,"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":0.7826336026191711},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6992479562759399},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5863213539123535},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.5853706002235413},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5779483318328857},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5480459332466125},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5367034673690796},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4975791275501251},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.46711668372154236},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.426449179649353},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4127707779407501},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36585044860839844},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13011041283607483},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07815667986869812}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7826336026191711},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6992479562759399},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5863213539123535},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.5853706002235413},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5779483318328857},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5480459332466125},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5367034673690796},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4975791275501251},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.46711668372154236},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.426449179649353},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4127707779407501},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36585044860839844},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13011041283607483},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07815667986869812},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d16-1063","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d16-1063","pdf_url":"https://www.aclweb.org/anthology/D16-1063.pdf","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 2016 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d16-1063","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d16-1063","pdf_url":"https://www.aclweb.org/anthology/D16-1063.pdf","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 2016 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963186170.pdf","grobid_xml":"https://content.openalex.org/works/W2963186170.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1495323440","https://openalex.org/W1532325895","https://openalex.org/W1614298861","https://openalex.org/W1615991656","https://openalex.org/W1854884267","https://openalex.org/W1882112236","https://openalex.org/W1980147176","https://openalex.org/W1982032418","https://openalex.org/W1987063155","https://openalex.org/W2002257715","https://openalex.org/W2026487812","https://openalex.org/W2044442377","https://openalex.org/W2053921957","https://openalex.org/W2099111195","https://openalex.org/W2103093728","https://openalex.org/W2113651538","https://openalex.org/W2117130368","https://openalex.org/W2118599489","https://openalex.org/W2125031621","https://openalex.org/W2127265454","https://openalex.org/W2128385268","https://openalex.org/W2133564696","https://openalex.org/W2137735870","https://openalex.org/W2141399712","https://openalex.org/W2170682101","https://openalex.org/W2250539671","https://openalex.org/W2250683455","https://openalex.org/W2251012068","https://openalex.org/W2251830157","https://openalex.org/W2950133940","https://openalex.org/W2951320349","https://openalex.org/W2951527505","https://openalex.org/W2951683451","https://openalex.org/W2962796133","https://openalex.org/W2964308564","https://openalex.org/W4231934124","https://openalex.org/W4294170691"],"related_works":["https://openalex.org/W2119384858","https://openalex.org/W947140380","https://openalex.org/W4286432911","https://openalex.org/W4230884544","https://openalex.org/W4245453790","https://openalex.org/W3194985222","https://openalex.org/W3216571906","https://openalex.org/W4214830338","https://openalex.org/W2518587255","https://openalex.org/W4287599800"],"abstract_inverted_index":{"Embedding":[0],"words":[1],"in":[2,12,79,102],"a":[3,8,25,48,67,135,165],"vector":[4],"space":[5],"has":[6],"gained":[7],"lot":[9],"of":[10,21,56,98,174],"attention":[11,82],"recent":[13],"years.":[14],"While":[15],"stateof-the-art":[16],"methods":[17,159],"provide":[18],"efficient":[19],"computation":[20],"word":[22,41,74,103,106,117,167],"similarities":[23],"via":[24,76,91],"low-dimensional":[26],"matrix":[27],"embedding,":[28],"their":[29],"motivation":[30],"is":[31,100,122,142,176],"often":[32],"left":[33],"unclear.":[34],"In":[35],"this":[36,63],"paper,":[37],"we":[38,65],"argue":[39],"that":[40,71],"embedding":[42,118],"can":[43],"be":[44],"naturally":[45],"viewed":[46],"as":[47,155,157],"ranking":[49,54,94],"problem":[50],"due":[51],"to":[52,86,114,125],"the":[53,57,81,92,110,115,126,139],"nature":[55],"evaluation":[58],"metrics.":[59],"Then,":[60],"based":[61],"on":[62,128,164],"insight,":[64],"propose":[66],"novel":[68],"framework":[69],"Wor-dRank":[70],"efficiently":[72],"estimates":[73],"representations":[75],"robust":[77],"ranking,":[78],"which":[80],"mechanism":[83],"and":[84,105,109,146],"robustness":[85],"noise":[87],"are":[88,112],"readily":[89],"achieved":[90],"DCG-like":[93],"losses.":[95],"The":[96],"performance":[97],"WordRank":[99,152,175],"measured":[101],"similarity":[104,168],"analogy":[107],"benchmarks,":[108],"results":[111],"compared":[113],"state-of-the-art":[116],"techniques.":[119],"Our":[120,170],"algorithm":[121],"very":[123],"competitive":[124],"state-of-the-arts":[127],"large":[129],"corpora,":[130],"while":[131],"outperforms":[132],"them":[133],"by":[134],"significant":[136],"margin":[137],"when":[138],"training":[140],"set":[141],"limited":[143],"(i.e.,":[144],"sparse":[145],"noisy).":[147],"With":[148],"17":[149],"million":[150],"tokens,":[151],"performs":[153],"almost":[154],"well":[156],"existing":[158],"using":[160],"7.2":[161],"billion":[162],"tokens":[163],"popular":[166],"benchmark.":[169],"multi-node":[171],"distributed":[172],"implementation":[173],"publicly":[177],"available":[178],"for":[179],"general":[180],"usage.":[181]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}