{"id":"https://openalex.org/W2962951088","doi":"https://doi.org/10.18653/v1/d17-1025","title":"Learning Chinese Word Representations From Glyphs Of Characters","display_name":"Learning Chinese Word Representations From Glyphs Of Characters","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2962951088","doi":"https://doi.org/10.18653/v1/d17-1025","mag":"2962951088"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d17-1025","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1025","pdf_url":"https://www.aclweb.org/anthology/D17-1025.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 2017 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/D17-1025.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079441176","display_name":"Tzu-Ray Su","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tzu-ray Su","raw_affiliation_strings":["Dept. of Electrical Engineering, National Taiwan University No. 1, Sec. 4, Roosevelt Road, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical Engineering, National Taiwan University No. 1, Sec. 4, Roosevelt Road, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040508737","display_name":"Hung-yi Lee","orcid":"https://orcid.org/0000-0002-9654-5747"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Hung-yi Lee","raw_affiliation_strings":["Dept. of Electrical Engineering, National Taiwan University No. 1, Sec. 4, Roosevelt Road, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical Engineering, National Taiwan University No. 1, Sec. 4, Roosevelt Road, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5040508737"],"corresponding_institution_ids":["https://openalex.org/I16733864"],"apc_list":null,"apc_paid":null,"fwci":7.8007,"has_fulltext":true,"cited_by_count":85,"citation_normalized_percentile":{"value":0.97866417,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"264","last_page":"273"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","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/T10181","display_name":"Natural Language Processing Techniques","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/T10028","display_name":"Topic Modeling","score":0.9983999729156494,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/glyph","display_name":"Glyph (data visualization)","score":0.9756741523742676},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8324099779129028},{"id":"https://openalex.org/keywords/chinese-characters","display_name":"Chinese characters","score":0.7836319804191589},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.7451213598251343},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6989500522613525},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6587691307067871},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6383794546127319},{"id":"https://openalex.org/keywords/font","display_name":"Font","score":0.5679693818092346},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5407786965370178},{"id":"https://openalex.org/keywords/bitmap","display_name":"Bitmap","score":0.48557206988334656},{"id":"https://openalex.org/keywords/kanji","display_name":"Kanji","score":0.4605696499347687},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.25963205099105835},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.23715263605117798},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08985289931297302}],"concepts":[{"id":"https://openalex.org/C142816647","wikidata":"https://www.wikidata.org/wiki/Q5573018","display_name":"Glyph (data visualization)","level":3,"score":0.9756741523742676},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8324099779129028},{"id":"https://openalex.org/C2781051154","wikidata":"https://www.wikidata.org/wiki/Q8201","display_name":"Chinese characters","level":2,"score":0.7836319804191589},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.7451213598251343},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6989500522613525},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6587691307067871},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6383794546127319},{"id":"https://openalex.org/C2777737414","wikidata":"https://www.wikidata.org/wiki/Q4868296","display_name":"Font","level":2,"score":0.5679693818092346},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5407786965370178},{"id":"https://openalex.org/C3115412","wikidata":"https://www.wikidata.org/wiki/Q1194708","display_name":"Bitmap","level":2,"score":0.48557206988334656},{"id":"https://openalex.org/C83535845","wikidata":"https://www.wikidata.org/wiki/Q82772","display_name":"Kanji","level":3,"score":0.4605696499347687},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.25963205099105835},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.23715263605117798},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08985289931297302},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d17-1025","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1025","pdf_url":"https://www.aclweb.org/anthology/D17-1025.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d17-1025","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1025","pdf_url":"https://www.aclweb.org/anthology/D17-1025.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2962951088.pdf","grobid_xml":"https://content.openalex.org/works/W2962951088.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1486649854","https://openalex.org/W1594229598","https://openalex.org/W1614298861","https://openalex.org/W1615991656","https://openalex.org/W1662133657","https://openalex.org/W1832693441","https://openalex.org/W1854884267","https://openalex.org/W1912843035","https://openalex.org/W1978400666","https://openalex.org/W2130942839","https://openalex.org/W2136655611","https://openalex.org/W2140679639","https://openalex.org/W2141200610","https://openalex.org/W2153579005","https://openalex.org/W2157331557","https://openalex.org/W2158899491","https://openalex.org/W2170240176","https://openalex.org/W2176412452","https://openalex.org/W2187089797","https://openalex.org/W2250539671","https://openalex.org/W2251811146","https://openalex.org/W2252143362","https://openalex.org/W2394700483","https://openalex.org/W2468476969","https://openalex.org/W2566150155","https://openalex.org/W2952230511","https://openalex.org/W2963012544","https://openalex.org/W2963285578","https://openalex.org/W2964325863","https://openalex.org/W4285719527","https://openalex.org/W4294170691"],"related_works":["https://openalex.org/W2968166662","https://openalex.org/W1616840082","https://openalex.org/W4320561754","https://openalex.org/W2149918773","https://openalex.org/W4386270415","https://openalex.org/W418410444","https://openalex.org/W2250289928","https://openalex.org/W2511147166","https://openalex.org/W2368258406","https://openalex.org/W3189048987"],"abstract_inverted_index":{"In":[0],"this":[1,87],"paper,":[2],"we":[3,44,91],"propose":[4,45],"new":[5],"methods":[6],"to":[7,30],"learn":[8],"Chinese":[9,12,28,74,98],"word":[10,36,49,75],"representations.":[11],"characters":[13,65],"are":[14,58,78],"composed":[15],"of":[16,34,64],"graphical":[17,39],"components,":[18],"which":[19,77],"carry":[20],"rich":[21],"semantics.":[22],"It":[23],"is":[24,89],"common":[25],"for":[26],"a":[27,35,42],"learner":[29],"comprehend":[31],"the":[32,62,70],"meaning":[33],"from":[37,61],"these":[38],"components.":[40],"As":[41],"result,":[43],"models":[46],"that":[47,90],"enhance":[48],"representations":[50,76],"by":[51,66,81],"character":[52,55,82],"glyphs.":[53],"The":[54],"glyph":[56,71],"features":[57,72],"directly":[59],"learned":[60],"bitmaps":[63],"convolutional":[67],"auto-encoder(convAE),":[68],"and":[69,99],"improve":[73],"already":[79],"enhanced":[80],"embeddings.":[83],"Another":[84],"contribution":[85],"in":[86,96],"paper":[88],"created":[92],"several":[93],"evaluation":[94],"datasets":[95],"traditional":[97],"made":[100],"them":[101],"public.":[102]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":19},{"year":2018,"cited_by_count":11}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}