{"id":"https://openalex.org/W2948375400","doi":"https://doi.org/10.18653/v1/p19-1489","title":"A Resource-Free Evaluation Metric for Cross-Lingual Word Embeddings Based on Graph Modularity","display_name":"A Resource-Free Evaluation Metric for Cross-Lingual Word Embeddings Based on Graph Modularity","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2948375400","doi":"https://doi.org/10.18653/v1/p19-1489","mag":"2948375400"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-1489","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1489","pdf_url":"https://www.aclweb.org/anthology/P19-1489.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P19-1489.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061166481","display_name":"Yoshinari Fujinuma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yoshinari Fujinuma","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081307846","display_name":"Jordan Boyd\u2010Graber","orcid":"https://orcid.org/0000-0002-7770-4431"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jordan Boyd-Graber","raw_affiliation_strings":["University of Maryland - College Park"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland - College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013872183","display_name":"Michael J. Paul","orcid":"https://orcid.org/0000-0002-9149-7539"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]},{"id":"https://openalex.org/I2802236040","display_name":"University of Colorado System","ror":"https://ror.org/00jc20583","country_code":"US","type":"education","lineage":["https://openalex.org/I2802236040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael J. Paul","raw_affiliation_strings":["University of Colorado Boulder"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Colorado Boulder","institution_ids":["https://openalex.org/I188538660","https://openalex.org/I2802236040"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4952","last_page":"4962"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9968000054359436,"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":0.9955000281333923,"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/modularity","display_name":"Modularity (biology)","score":0.7745707035064697},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.752862811088562},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6943953633308411},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6163305044174194},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5653036832809448},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5429927110671997},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5429543852806091},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.46141064167022705},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4605698883533478},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.28798991441726685},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20698091387748718}],"concepts":[{"id":"https://openalex.org/C2779478453","wikidata":"https://www.wikidata.org/wiki/Q6889748","display_name":"Modularity (biology)","level":2,"score":0.7745707035064697},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.752862811088562},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6943953633308411},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6163305044174194},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5653036832809448},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5429927110671997},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5429543852806091},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.46141064167022705},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4605698883533478},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28798991441726685},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20698091387748718},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"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/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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/v1/p19-1489","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1489","pdf_url":"https://www.aclweb.org/anthology/P19-1489.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},{"id":"mag:2948375400","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1906.01926.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1906.01926","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1906.01926","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.18653/v1/p19-1489","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1489","pdf_url":"https://www.aclweb.org/anthology/P19-1489.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/8"}],"awards":[{"id":"https://openalex.org/G211012689","display_name":null,"funder_award_id":"HR0011-15-C-0113","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G5034896428","display_name":"CHS: Medium: Hyperlocal and Hypertemporal Information in Mass Emergencies Events: Next Generation Crisis Informatics Data Collection and Analytics","funder_award_id":"1564275","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6041586732","display_name":null,"funder_award_id":"IIS-1564275","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320307943","display_name":"Raytheon Company","ror":"https://ror.org/0354t7b78"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2948375400.pdf","grobid_xml":"https://content.openalex.org/works/W2948375400.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W165283731","https://openalex.org/W168564468","https://openalex.org/W342285082","https://openalex.org/W1731081199","https://openalex.org/W1875112053","https://openalex.org/W1983345514","https://openalex.org/W2008652694","https://openalex.org/W2033193852","https://openalex.org/W2033593667","https://openalex.org/W2041532239","https://openalex.org/W2057069782","https://openalex.org/W2065157922","https://openalex.org/W2095293504","https://openalex.org/W2118123209","https://openalex.org/W2126725946","https://openalex.org/W2130339025","https://openalex.org/W2147946282","https://openalex.org/W2150102617","https://openalex.org/W2153579005","https://openalex.org/W2175002614","https://openalex.org/W2187089797","https://openalex.org/W2216065124","https://openalex.org/W2250473257","https://openalex.org/W2250533720","https://openalex.org/W2250600805","https://openalex.org/W2251033195","https://openalex.org/W2251066368","https://openalex.org/W2270364989","https://openalex.org/W2282830431","https://openalex.org/W2293491541","https://openalex.org/W2294774419","https://openalex.org/W2493916176","https://openalex.org/W2497040301","https://openalex.org/W2508069829","https://openalex.org/W2561995736","https://openalex.org/W2573062194","https://openalex.org/W2626534681","https://openalex.org/W2740132093","https://openalex.org/W2741602058","https://openalex.org/W2887838996","https://openalex.org/W2949531524","https://openalex.org/W2962684168","https://openalex.org/W2962795068","https://openalex.org/W2962824887","https://openalex.org/W2963047628","https://openalex.org/W2963118869","https://openalex.org/W2963165489","https://openalex.org/W2963602293","https://openalex.org/W2964266061","https://openalex.org/W2964325543","https://openalex.org/W3104723404"],"related_works":["https://openalex.org/W2962712421","https://openalex.org/W3175523938","https://openalex.org/W2949941041","https://openalex.org/W3213534368","https://openalex.org/W2962883166","https://openalex.org/W2614551030","https://openalex.org/W3176462054","https://openalex.org/W3030196214","https://openalex.org/W2980406419","https://openalex.org/W2108061274","https://openalex.org/W2264869955","https://openalex.org/W3025519005","https://openalex.org/W2941076272","https://openalex.org/W2999470854","https://openalex.org/W2937280085","https://openalex.org/W2989798563","https://openalex.org/W2794132063","https://openalex.org/W2557444973","https://openalex.org/W2579644692","https://openalex.org/W2986907052"],"abstract_inverted_index":{"Cross-lingual":[0],"word":[1,25,32,115],"embeddings":[2,90],"encode":[3],"the":[4,62,87],"meaning":[5],"of":[6,30,64,89],"words":[7,47],"from":[8],"different":[9],"languages":[10],"into":[11],"a":[12,57,67,71],"shared":[13],"low-dimensional":[14],"space.":[15],"An":[16],"important":[17],"requirement":[18],"for":[19],"many":[20],"downstream":[21,78],"tasks":[22],"is":[23,83],"that":[24,60,102],"similarity":[26],"should":[27,37],"be":[28,39],"independent":[29],"language-i.e.,":[31],"vectors":[33],"within":[34],"one":[35],"language":[36,120],"not":[38,93],"more":[40],"similar":[41],"to":[42,46,73,111],"each":[43],"other":[44],"than":[45],"in":[48,66,122],"another":[49],"language.":[50],"We":[51,98],"measure":[52],"this":[53],"characteristic":[54],"using":[55],"modularity,":[56],"network":[58],"measurement":[59],"measures":[61],"strength":[63],"clusters":[65],"graph.":[68],"Modularity":[69],"has":[70],"moderate":[72],"strong":[74],"correlation":[75],"with":[76],"three":[77],"tasks,":[79],"even":[80],"though":[81],"modularity":[82,103],"based":[84],"only":[85],"on":[86,118],"structure":[88],"and":[91],"does":[92],"require":[94],"any":[95],"external":[96],"resources.":[97],"show":[99],"through":[100],"experiments":[101],"can":[104],"serve":[105],"as":[106],"an":[107],"intrinsic":[108],"validation":[109],"metric":[110],"improve":[112],"unsupervised":[113],"cross-lingual":[114],"embeddings,":[116],"particularly":[117],"distant":[119],"pairs":[121],"low-resource":[123],"settings.":[124],"1":[125]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}
