{"id":"https://openalex.org/W2899277986","doi":"https://doi.org/10.18653/v1/k18-1041","title":"Resources to Examine the Quality of Word Embedding Models Trained on n-Gram Data","display_name":"Resources to Examine the Quality of Word Embedding Models Trained on n-Gram Data","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2899277986","doi":"https://doi.org/10.18653/v1/k18-1041","mag":"2899277986"},"language":"en","primary_location":{"id":"doi:10.18653/v1/k18-1041","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k18-1041","pdf_url":"https://www.aclweb.org/anthology/K18-1041.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 22nd Conference on Computational Natural Language Learning","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/K18-1041.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080414309","display_name":"\u00c1bel Elekes","orcid":"https://orcid.org/0000-0003-3538-9469"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"\u00c1bel Elekes","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053128825","display_name":"Adrian Englhardt","orcid":"https://orcid.org/0000-0002-0388-1785"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Adrian Englhardt","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033950182","display_name":"Martin Sch\u00e4ler","orcid":"https://orcid.org/0000-0003-1671-6508"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Martin Sch\u00e4ler","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049768806","display_name":"Klemens B\u00f6hm","orcid":"https://orcid.org/0000-0002-1706-1913"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Klemens B\u00f6hm","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5080414309"],"corresponding_institution_ids":["https://openalex.org/I102335020"],"apc_list":null,"apc_paid":null,"fwci":0.4887,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.73629264,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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/T12031","display_name":"Speech and dialogue systems","score":0.9970999956130981,"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":0.8140155673027039},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.7400075793266296},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.7293829321861267},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6883055567741394},{"id":"https://openalex.org/keywords/n-gram","display_name":"n-gram","score":0.6843540668487549},{"id":"https://openalex.org/keywords/scripting-language","display_name":"Scripting language","score":0.6020787358283997},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.5901486873626709},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5783091187477112},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5425369143486023},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5160255432128906},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.50380939245224},{"id":"https://openalex.org/keywords/distributional-semantics","display_name":"Distributional semantics","score":0.49644404649734497},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4875328242778778},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.346265971660614},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3428969979286194},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.23435375094413757},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.13771161437034607}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8140155673027039},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.7400075793266296},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.7293829321861267},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6883055567741394},{"id":"https://openalex.org/C117884012","wikidata":"https://www.wikidata.org/wiki/Q94489","display_name":"n-gram","level":3,"score":0.6843540668487549},{"id":"https://openalex.org/C61423126","wikidata":"https://www.wikidata.org/wiki/Q187432","display_name":"Scripting language","level":2,"score":0.6020787358283997},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.5901486873626709},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5783091187477112},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5425369143486023},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5160255432128906},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.50380939245224},{"id":"https://openalex.org/C2778828372","wikidata":"https://www.wikidata.org/wiki/Q5283209","display_name":"Distributional semantics","level":3,"score":0.49644404649734497},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4875328242778778},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.346265971660614},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3428969979286194},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.23435375094413757},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.13771161437034607},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/k18-1041","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k18-1041","pdf_url":"https://www.aclweb.org/anthology/K18-1041.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 22nd Conference on Computational Natural Language Learning","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/k18-1041","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k18-1041","pdf_url":"https://www.aclweb.org/anthology/K18-1041.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 22nd Conference on Computational Natural Language Learning","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2899277986.pdf","grobid_xml":"https://content.openalex.org/works/W2899277986.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1498740961","https://openalex.org/W1539309091","https://openalex.org/W1570098300","https://openalex.org/W1598683382","https://openalex.org/W1614298861","https://openalex.org/W1615991656","https://openalex.org/W1854884267","https://openalex.org/W1937075317","https://openalex.org/W2019096529","https://openalex.org/W2026487812","https://openalex.org/W2038634595","https://openalex.org/W2053921957","https://openalex.org/W2067438047","https://openalex.org/W2080100102","https://openalex.org/W2102343050","https://openalex.org/W2117065474","https://openalex.org/W2125031621","https://openalex.org/W2126725946","https://openalex.org/W2137735870","https://openalex.org/W2153579005","https://openalex.org/W2202042777","https://openalex.org/W2250539671","https://openalex.org/W2250879510","https://openalex.org/W2251012068","https://openalex.org/W2251803266","https://openalex.org/W2252211741","https://openalex.org/W2292415828","https://openalex.org/W2512498397","https://openalex.org/W2516007590","https://openalex.org/W2527896214","https://openalex.org/W2576614118","https://openalex.org/W2585950056","https://openalex.org/W2596026555","https://openalex.org/W2611669587","https://openalex.org/W2612622926","https://openalex.org/W2963099212","https://openalex.org/W2963780471","https://openalex.org/W4254304201","https://openalex.org/W4294170691"],"related_works":["https://openalex.org/W2250909759","https://openalex.org/W2532616038","https://openalex.org/W2624072012","https://openalex.org/W2787311093","https://openalex.org/W2057384730","https://openalex.org/W4307474317","https://openalex.org/W2008468404","https://openalex.org/W2147879411","https://openalex.org/W2132221452","https://openalex.org/W2899277986"],"abstract_inverted_index":{"Word":[0],"embeddings":[1],"are":[2,24,68],"powerful":[3],"tools":[4],"that":[5,155],"facilitate":[6],"better":[7],"analysis":[8],"of":[9,69,92,96,106,128],"natural":[10],"language.":[11],"However,":[12,37],"their":[13],"quality":[14,136,161],"highly":[15],"depends":[16],"on":[17,28],"the":[18,33,46,52,61,64,93,100,103,134],"resource":[19,86,101,144],"used":[20,108,115],"for":[21,51,116,162],"training.":[22],"There":[23],"various":[25],"approaches":[26],"relying":[27],"n-gram":[29,35],"corpora,":[30,109],"such":[31],"as":[32,110,112],"Google":[34,53],"corpus.":[36],"ngram":[38],"corpora":[39],"only":[40],"offer":[41],"a":[42,85,126],"small":[43],"window":[44],"into":[45],"full":[47],"text":[48],"-5":[49],"words":[50],"corpus":[54,117],"at":[55],"best.":[56],"This":[57],"gives":[58],"way":[59],"to":[60,132,145],"concern":[62,78],"whether":[63],"extracted":[65],"word":[66],"semantics":[67],"high":[70,160],"quality.":[71],"In":[72],"this":[73,77],"paper,":[74],"we":[75,83,124],"address":[76],"with":[79,164],"two":[80],"contributions.":[81],"First,":[82],"provide":[84],"containing":[87],"120":[88],"word-embedding":[89],"models":[90],"-one":[91],"largest":[94],"collection":[95],"embedding":[97],"models.":[98],"Furthermore,":[99],"contains":[102],"ngramed":[104],"versions":[105],"all":[107],"well":[111],"our":[113,143],"scripts":[114],"generation,":[118],"model":[119],"generation":[120],"and":[121,149],"evaluation.":[122],"Second,":[123],"define":[125],"set":[127],"meaningful":[129],"experiments":[130,141],"allowing":[131],"evaluate":[133],"aforementioned":[135],"differences.":[137],"We":[138],"conduct":[139],"these":[140],"using":[142],"show":[146],"its":[147],"usage":[148],"significance.":[150],"The":[151],"evaluation":[152],"results":[153],"confirm":[154],"one":[156],"generally":[157],"can":[158],"expect":[159],"n-grams":[163],"n":[165],"3.":[166]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}