{"id":"https://openalex.org/W2943357157","doi":"https://doi.org/10.23919/icact.2019.8701980","title":"Domain Specific NMT based on Knowledge Graph Embedding and Attention","display_name":"Domain Specific NMT based on Knowledge Graph Embedding and Attention","publication_year":2019,"publication_date":"2019-02-01","ids":{"openalex":"https://openalex.org/W2943357157","doi":"https://doi.org/10.23919/icact.2019.8701980","mag":"2943357157"},"language":"en","primary_location":{"id":"doi:10.23919/icact.2019.8701980","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icact.2019.8701980","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 21st International Conference on Advanced Communication Technology (ICACT)","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/A5075211218","display_name":"Hao Yang","orcid":"https://orcid.org/0000-0003-3020-9828"},"institutions":[{"id":"https://openalex.org/I4210146936","display_name":"Huawei Technologies (United States)","ror":"https://ror.org/03jyqk712","country_code":"US","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210146936"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hao Yang","raw_affiliation_strings":["2012 Labs, Huawei Technologies CO., LTD"],"affiliations":[{"raw_affiliation_string":"2012 Labs, Huawei Technologies CO., LTD","institution_ids":["https://openalex.org/I4210146936"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020557320","display_name":"Gengui Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I4210146936","display_name":"Huawei Technologies (United States)","ror":"https://ror.org/03jyqk712","country_code":"US","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210146936"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gengui Xie","raw_affiliation_strings":["2012 Labs, Huawei Technologies CO., LTD"],"affiliations":[{"raw_affiliation_string":"2012 Labs, Huawei Technologies CO., LTD","institution_ids":["https://openalex.org/I4210146936"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013250925","display_name":"Ying Qin","orcid":"https://orcid.org/0000-0003-4606-7174"},"institutions":[{"id":"https://openalex.org/I4210146936","display_name":"Huawei Technologies (United States)","ror":"https://ror.org/03jyqk712","country_code":"US","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210146936"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ying Qin","raw_affiliation_strings":["2012 Labs, Huawei Technologies CO., LTD"],"affiliations":[{"raw_affiliation_string":"2012 Labs, Huawei Technologies CO., LTD","institution_ids":["https://openalex.org/I4210146936"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100616771","display_name":"Peng Song","orcid":"https://orcid.org/0000-0003-3093-0068"},"institutions":[{"id":"https://openalex.org/I4210146936","display_name":"Huawei Technologies (United States)","ror":"https://ror.org/03jyqk712","country_code":"US","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210146936"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Song Peng","raw_affiliation_strings":["2012 Labs, Huawei Technologies CO., LTD"],"affiliations":[{"raw_affiliation_string":"2012 Labs, Huawei Technologies CO., LTD","institution_ids":["https://openalex.org/I4210146936"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5075211218"],"corresponding_institution_ids":["https://openalex.org/I4210146936"],"apc_list":null,"apc_paid":null,"fwci":0.9801,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.81770817,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"516","last_page":"521"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9991999864578247,"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":0.9991999864578247,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9850000143051147,"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":0.8150310516357422},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7485033273696899},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.7371219396591187},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6516746282577515},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.5473478436470032},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.4848838746547699},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4711878299713135},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.452227383852005},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.45207950472831726},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.44555899500846863},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4071628153324127}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8150310516357422},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7485033273696899},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.7371219396591187},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6516746282577515},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.5473478436470032},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.4848838746547699},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4711878299713135},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.452227383852005},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.45207950472831726},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.44555899500846863},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4071628153324127},{"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/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/icact.2019.8701980","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icact.2019.8701980","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 21st International Conference on Advanced Communication Technology (ICACT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1532470117","https://openalex.org/W2062270497","https://openalex.org/W2126226055","https://openalex.org/W2161066414","https://openalex.org/W2251476947","https://openalex.org/W2461925906","https://openalex.org/W2594990650","https://openalex.org/W4245107743"],"related_works":["https://openalex.org/W2604454537","https://openalex.org/W2808284704","https://openalex.org/W2883748392","https://openalex.org/W2897702399","https://openalex.org/W4206028705","https://openalex.org/W2757431232","https://openalex.org/W2954554213","https://openalex.org/W3200431764","https://openalex.org/W4288286922","https://openalex.org/W4206547516"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"the":[3,17,66,75,97,132],"encoder-decoder/attention-based":[4],"Transformer":[5],"architecture":[6],"is":[7],"superior":[8],"to":[9],"traditional":[10,76],"methods":[11],"and":[12,50,61,70,99,127,137,150,160],"has":[13],"been":[14],"adopted":[15],"as":[16,46],"core":[18],"technology":[19],"in":[20,87,96],"Google":[21],"services.":[22],"But":[23],"for":[24],"specific":[25],"areas,":[26],"translation":[27,48,53],"accuracy":[28,86],"or":[29],"BLEU":[30,139],"scores":[31,140],"are":[32],"not":[33],"good":[34],"enough":[35,57],"without":[36],"domain":[37,43],"knowledge.":[38],"Typical":[39],"problems":[40],"include":[41],"(1)":[42],"entity":[44,107],"such":[45],"subject/object":[47],"error,":[49,54],"(2)":[51],"relationship":[52,108,161],"because":[55],"lacking":[56],"knowledge":[58,67,115],"involved":[59],"model":[60,72],"algorithms.":[62],"This":[63],"paper":[64],"introduces":[65],"graph":[68],"embedding":[69,95],"attention":[71,104,112],"based":[73],"on":[74],"encoder-decoder":[77],"model.":[78],"The":[79,102,121],"KG":[80,103,144,148],"embedded":[81],"layer":[82,105],"improve":[83,131],"entities":[84,93,159],"pair":[85,94],"diffident":[88],"languages,":[89],"by":[90,110],"softly":[91],"matching":[92],"encoder":[98],"decoder":[100],"steps.":[101],"leverages":[106],"pair,":[109],"trained":[111],"score":[113],"from":[114],"graph,":[116],"just":[117],"like":[118],"business":[119],"rules.":[120,162],"experiment":[122],"proves":[123],"Knowledge":[124],"Graph":[125],"Embedding":[126],"Attention":[128,149],"(KGEA)":[129],"can":[130],"ICT-NMT":[133],"online":[134],"production":[135],"system,":[136],"also":[138],"increase":[141],"6%":[142],"with":[143,147,154,157],"Embedding,":[145],"3%":[146],"total":[151],"7%,":[152],"compared":[153],"general-purpose":[155],"transformer,":[156],"semantic":[158]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2020,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}