{"id":"https://openalex.org/W2844166366","doi":null,"title":"Convolutional Neural Network for Universal Sentence Embeddings","display_name":"Convolutional Neural Network for Universal Sentence Embeddings","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2844166366","mag":"2844166366"},"language":"en","primary_location":{"id":"mag:2844166366","doi":null,"is_oa":false,"landing_page_url":"https://www.aclweb.org/anthology/C18-1209.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419219","display_name":"International Conference on Computational Linguistics","issn_l":"1525-2477","issn":["1525-2477"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Computational Linguistics","raw_type":null},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"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/A5101038769","display_name":"Xiaoqi Jiao","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoqi Jiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022502922","display_name":"Fang Wang","orcid":"https://orcid.org/0000-0001-6170-0463","observed_orcids":["https://orcid.org/0000-0001-6170-0463","https://orcid.org/0009-0008-9678-8205"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang Wang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-6170-0463","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5057421680","display_name":"Dan Feng","orcid":"https://orcid.org/0000-0002-4674-6006","observed_orcids":["https://orcid.org/0000-0002-4674-6006"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dan Feng","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-4674-6006","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4423,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.64956476,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2470","last_page":"2481"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9945999979972839,"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":0.9945999979972839,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.0012000000569969416,"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":0.0010000000474974513,"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/sentence-embeddings","display_name":"sentence embeddings","score":0.9509999752044678},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.8709999918937683},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.6899999976158142},{"id":"https://openalex.org/keywords/n-gram-features","display_name":"n-gram features","score":0.8090000152587891},{"id":"https://openalex.org/keywords/word-embeddings","display_name":"word embeddings","score":0.7950000166893005},{"id":"https://openalex.org/keywords/bag-of-words-model","display_name":"bag-of-words model","score":0.7360000014305115},{"id":"https://openalex.org/keywords/pre-trained-embeddings","display_name":"pre-trained embeddings","score":0.574999988079071},{"id":"https://openalex.org/keywords/parameter-initialization","display_name":"parameter initialization","score":0.6159999966621399}],"concepts":[{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.8709540367126465},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7927353382110596},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7176846265792847},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7073714733123779},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6311492919921875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6281189918518066},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6046193838119507},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5684948563575745},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5467807054519653},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4207564890384674},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34627896547317505},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11211690306663513},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2844166366","doi":null,"is_oa":false,"landing_page_url":"https://www.aclweb.org/anthology/C18-1209.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419219","display_name":"International Conference on Computational Linguistics","issn_l":"1525-2477","issn":["1525-2477"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Computational Linguistics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1486649854","https://openalex.org/W1604489931","https://openalex.org/W1814992895","https://openalex.org/W1832693441","https://openalex.org/W1889268436","https://openalex.org/W1924770834","https://openalex.org/W2064675550","https://openalex.org/W2095705004","https://openalex.org/W2103305545","https://openalex.org/W2104246439","https://openalex.org/W2106612368","https://openalex.org/W2112796928","https://openalex.org/W2120615054","https://openalex.org/W2126400076","https://openalex.org/W2131744502","https://openalex.org/W2133458109","https://openalex.org/W2137607259","https://openalex.org/W2138238299","https://openalex.org/W2152180407","https://openalex.org/W2155484602","https://openalex.org/W2250307601","https://openalex.org/W2251044566","https://openalex.org/W2251427843","https://openalex.org/W2251861449","https://openalex.org/W2251869843","https://openalex.org/W2251919380","https://openalex.org/W2251939518","https://openalex.org/W2252215182","https://openalex.org/W2271328876","https://openalex.org/W2294860948","https://openalex.org/W2462305634","https://openalex.org/W2517782820","https://openalex.org/W2597655663","https://openalex.org/W2605035112","https://openalex.org/W2611248707","https://openalex.org/W2952230511","https://openalex.org/W2963436889","https://openalex.org/W2963499246","https://openalex.org/W2964121744"],"related_works":["https://openalex.org/W2794557536","https://openalex.org/W2429488962","https://openalex.org/W4387521241","https://openalex.org/W2543875770","https://openalex.org/W2804950321","https://openalex.org/W2612953412","https://openalex.org/W3023305215","https://openalex.org/W4416076257","https://openalex.org/W4220923972","https://openalex.org/W2961915345"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,35,41,55,86],"simple":[4],"CNN":[5],"model":[6,71],"for":[7,25],"creating":[8],"general-purpose":[9],"sentence":[10,36,49,125],"embeddings":[11,31],"that":[12,96],"can":[13,19],"transfer":[14,104],"easily":[15],"across":[16],"domains":[17],"and":[18,44,78,107],"also":[20],"act":[21],"as":[22],"effective":[23],"initialization":[24],"downstream":[26],"tasks.":[27],"Recently,":[28],"averaging":[29],"the":[30,109,112,120,123],"of":[32,47,60,62,76,88,111],"words":[33,63,77],"in":[34,58,66,103,114],"has":[37],"proven":[38],"to":[39,80],"be":[40],"surprisingly":[42],"successful":[43],"efficient":[45],"way":[46],"obtaining":[48],"embeddings.":[50,126],"However,":[51],"these":[52,89],"models":[53,102],"represent":[54],"sentence,":[56],"only":[57],"terms":[59],"features":[61,75],"or":[64],"uni-grams":[65],"it.":[67],"In":[68],"contrast,":[69],"our":[70],"(CSE)":[72],"utilizes":[73],"both":[74],"n-grams":[79],"encode":[81],"sentences,":[82],"which":[83],"is":[84],"actually":[85],"generalization":[87],"bag-of-words":[90],"models.":[91],"The":[92],"extensive":[93],"experiments":[94],"demonstrate":[95],"CSE":[97],"performs":[98],"better":[99],"than":[100],"average":[101],"learning":[105,116],"setting":[106,117],"exceeds":[108],"state":[110],"art":[113],"supervised":[115],"by":[118],"initializing":[119],"parameters":[121],"with":[122],"pre-trained":[124]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2018-07-19T00:00:00"}