{"id":"https://openalex.org/W2807264817","doi":"https://doi.org/10.18653/v1/s18-1161","title":"UNAM at SemEval-2018 Task 10: Unsupervised Semantic Discriminative Attribute Identification in Neural Word Embedding Cones","display_name":"UNAM at SemEval-2018 Task 10: Unsupervised Semantic Discriminative Attribute Identification in Neural Word Embedding Cones","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2807264817","doi":"https://doi.org/10.18653/v1/s18-1161","mag":"2807264817"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s18-1161","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s18-1161","pdf_url":"https://www.aclweb.org/anthology/S18-1161.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 12th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/S18-1161.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067382725","display_name":"Ignacio Arroyo\u2010Fern\u00e1ndez","orcid":"https://orcid.org/0000-0002-2866-1316"},"institutions":[{"id":"https://openalex.org/I8961855","display_name":"Universidad Nacional Aut\u00f3noma de M\u00e9xico","ror":"https://ror.org/01tmp8f25","country_code":"MX","type":"education","lineage":["https://openalex.org/I8961855"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Ignacio Arroyo-Fern\u00e1ndez","raw_affiliation_strings":["Universidad Nacional Aut\u00f3noma de M\u00e9xico (UNAM)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidad Nacional Aut\u00f3noma de M\u00e9xico (UNAM)","institution_ids":["https://openalex.org/I8961855"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083331228","display_name":"Iv\u00e1n Meza","orcid":"https://orcid.org/0000-0002-7239-1480"},"institutions":[{"id":"https://openalex.org/I4210098917","display_name":"Instituto de Investigaciones en Ciencias de la Salud","ror":"https://ror.org/00vsnbn30","country_code":"AR","type":"facility","lineage":["https://openalex.org/I151201029","https://openalex.org/I166401450","https://openalex.org/I4210098917","https://openalex.org/I4210123736","https://openalex.org/I4210130626","https://openalex.org/I4387155568"]}],"countries":["AR"],"is_corresponding":false,"raw_author_name":"Ivan Meza","raw_affiliation_strings":["Instituto de Investigaciones en Matemticas Aplicadas y en Sistemas -UNAM","Instituto de Investigaciones en Matem\u00e1ticas Aplicadas y en Sistemas -UNAM"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto de Investigaciones en Matemticas Aplicadas y en Sistemas -UNAM","institution_ids":["https://openalex.org/I4210098917"]},{"raw_affiliation_string":"Instituto de Investigaciones en Matem\u00e1ticas Aplicadas y en Sistemas -UNAM","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Carlos-Francisco Me\u00e9ndez-Cruz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carlos-Francisco Me\u00e9ndez-Cruz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"977","last_page":"984"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9988999962806702,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9711999893188477,"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/discriminative-model","display_name":"Discriminative model","score":0.7186009287834167},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.6640651822090149},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5927674174308777},{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.5884053111076355},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5825626850128174},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5494465827941895},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49082741141319275},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.46301719546318054},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.45665159821510315},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.42195001244544983},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.3834356665611267},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.37257611751556396},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3372896611690521},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3314022123813629},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.2640148401260376}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7186009287834167},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.6640651822090149},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5927674174308777},{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.5884053111076355},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5825626850128174},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5494465827941895},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49082741141319275},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.46301719546318054},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.45665159821510315},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.42195001244544983},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.3834356665611267},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.37257611751556396},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3372896611690521},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3314022123813629},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2640148401260376},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/s18-1161","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s18-1161","pdf_url":"https://www.aclweb.org/anthology/S18-1161.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 12th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/s18-1161","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s18-1161","pdf_url":"https://www.aclweb.org/anthology/S18-1161.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 12th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2807264817.pdf","grobid_xml":"https://content.openalex.org/works/W2807264817.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W146395692","https://openalex.org/W1503259811","https://openalex.org/W1528802670","https://openalex.org/W1996309403","https://openalex.org/W2024197741","https://openalex.org/W2035535858","https://openalex.org/W2051885446","https://openalex.org/W2078894097","https://openalex.org/W2083303100","https://openalex.org/W2098411764","https://openalex.org/W2117545199","https://openalex.org/W2153579005","https://openalex.org/W2159487986","https://openalex.org/W2168565044","https://openalex.org/W2250539671","https://openalex.org/W2251771443","https://openalex.org/W2493916176","https://openalex.org/W2510150140","https://openalex.org/W2572487292","https://openalex.org/W2595340503","https://openalex.org/W2766034339","https://openalex.org/W2912565176","https://openalex.org/W2963176474","https://openalex.org/W2963553009","https://openalex.org/W2963740900","https://openalex.org/W3098865490","https://openalex.org/W3143107425","https://openalex.org/W4249965322","https://openalex.org/W4293470669","https://openalex.org/W4294170691"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W2805850807","https://openalex.org/W2805572527","https://openalex.org/W2469576572","https://openalex.org/W2751089246","https://openalex.org/W2753242182","https://openalex.org/W2507611421"],"abstract_inverted_index":{"In":[0],"this":[1,29],"paper":[2],"we":[3,31,108],"report":[4],"an":[5,12],"unsupervised":[6,38],"method":[7],"aimed":[8],"to":[9,114],"identify":[10],"whether":[11],"attribute":[13,52,65],"is":[14,75],"discriminative":[15],"for":[16,122,127],"two":[17,84],"words":[18],"(which":[19],"are":[20,102],"treated":[21],"as":[22,62],"concepts,":[23],"in":[24],"our":[25],"particular":[26],"case).":[27],"To":[28],"end,":[30],"use":[32],"geometrically":[33],"inspired":[34],"vector":[35,110],"operations":[36,111,120],"underlying":[37],"decision":[39,42],"functions.":[40],"These":[41],"functions":[43],"operate":[44],"on":[45],"stateof-the-art":[46],"neural":[47,105],"word":[48,106],"embeddings":[49],"of":[50],"the":[51,54,78,86,90,131,136],"and":[53,125,130,135,142],"concepts.":[55],"The":[56],"main":[57],"idea":[58],"can":[59],"be":[60],"described":[61,139],"follows:":[63],"if":[64],"q":[66,74,92,101,134],"discriminates":[67],"concept":[68,71],"a":[69,141],"from":[70,77],"b,":[72,100],"then":[73],"excluded":[76],"feature":[79],"set":[80,119],"shared":[81],"by":[82,140],"these":[83],"concepts:":[85],"intersection.":[87],"That":[88],"is,":[89],"membership":[91],"(a":[93],"b)":[94],"does":[95],"not":[96],"hold.":[97],"As":[98],"a,":[99],"represented":[103],"with":[104],"embeddings,":[107],"tested":[109],"allowing":[112],"us":[113],"measure":[115],"membership,":[116],"i.e.":[117],"fuzzy":[118,123,128],"(t-norm,":[121],"intersection,":[124],"t-conorm,":[126],"union)":[129],"similarity":[132],"between":[133],"convex":[137],"cone":[138],"b.":[143]},"counts_by_year":[{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
