{"id":"https://openalex.org/W4223963389","doi":"https://doi.org/10.1145/3523150.3523175","title":"Graph Convolution Word Embedding and Attention for Text Classification\u2217","display_name":"Graph Convolution Word Embedding and Attention for Text Classification\u2217","publication_year":2022,"publication_date":"2022-01-15","ids":{"openalex":"https://openalex.org/W4223963389","doi":"https://doi.org/10.1145/3523150.3523175"},"language":"en","primary_location":{"id":"doi:10.1145/3523150.3523175","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3523150.3523175","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 The 6th International Conference on Machine Learning and Soft Computing","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/A5010570582","display_name":"Yang Yi","orcid":"https://orcid.org/0000-0002-9989-6657"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yi Yang","raw_affiliation_strings":["State Grid Shandong Electric Power Company, China"],"affiliations":[{"raw_affiliation_string":"State Grid Shandong Electric Power Company, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077203377","display_name":"Qihui Cui","orcid":"https://orcid.org/0000-0002-1861-4997"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qihui Cui","raw_affiliation_strings":["State Grid Shandong Electric Power Company, China"],"affiliations":[{"raw_affiliation_string":"State Grid Shandong Electric Power Company, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027406081","display_name":"Lijun Ji","orcid":"https://orcid.org/0000-0002-8709-8623"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lijun Ji","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052364647","display_name":"Zhuoran Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuoran Cheng","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5010570582"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5305,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.69624728,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"160","last_page":"166"},"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/T11273","display_name":"Advanced Graph Neural Networks","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/T11550","display_name":"Text and Document Classification Technologies","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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8136105537414551},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.8134438991546631},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7031747698783875},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6486911177635193},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.6054831147193909},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5818730592727661},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5696614384651184},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5567959547042847},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5031017661094666},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.45874011516571045},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4144671559333801},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.36375218629837036},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.19985631108283997},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09472936391830444}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8136105537414551},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.8134438991546631},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7031747698783875},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6486911177635193},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.6054831147193909},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5818730592727661},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5696614384651184},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5567959547042847},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5031017661094666},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.45874011516571045},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4144671559333801},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.36375218629837036},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.19985631108283997},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09472936391830444},{"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3523150.3523175","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3523150.3523175","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 The 6th International Conference on Machine Learning and Soft Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7400000095367432}],"awards":[{"id":"https://openalex.org/G6301984634","display_name":null,"funder_award_id":"2020A?074","funder_id":"https://openalex.org/F4320336324","funder_display_name":"State Grid Shandong Electric Power Company"}],"funders":[{"id":"https://openalex.org/F4320336324","display_name":"State Grid Shandong Electric Power Company","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W2064675550","https://openalex.org/W2070246124","https://openalex.org/W2788667846","https://openalex.org/W2891434004","https://openalex.org/W2963224980","https://openalex.org/W2971220558","https://openalex.org/W6682691769","https://openalex.org/W6715835459","https://openalex.org/W6751686549"],"related_works":["https://openalex.org/W4288407670","https://openalex.org/W947140380","https://openalex.org/W2911655849","https://openalex.org/W4286432911","https://openalex.org/W4230884544","https://openalex.org/W4245453790","https://openalex.org/W2726375170","https://openalex.org/W3194985222","https://openalex.org/W3216571906","https://openalex.org/W2785740378"],"abstract_inverted_index":{"Text":[0],"classification":[1,23,54,118],"is":[2,43,132,144],"an":[3,145],"important":[4,146],"and":[5,18,29,63,73,86,105],"classic":[6],"task":[7],"of":[8,76,97],"natural":[9],"language":[10],"processing.":[11],"Deep":[12],"neural":[13,41,99],"networks":[14,100],"are":[15],"becoming":[16],"more":[17,19,37],"popular":[20],"in":[21,90],"text":[22,53,78,117],"due":[24],"to":[25,148],"their":[26],"expressive":[27],"power":[28],"low":[30],"requirements":[31],"for":[32,46],"feature":[33],"engineering.":[34],"However,":[35],"the":[36,71,77,80,91,95,128,137,149],"flexible":[38],"graph":[39,59],"convolutional":[40],"network":[42],"rarely":[44],"used":[45],"this":[47],"task.":[48],"This":[49],"paper":[50],"proposes":[51],"a":[52],"model":[55,67],"(GENET)":[56],"based":[57],"on":[58,124],"convolution":[60],"word":[61,83,138,150],"embedding":[62,151],"attention":[64],"mechanism.":[65],"The":[66],"can":[68,106],"better":[69],"combine":[70],"semantic":[72,88],"lexical":[74],"information":[75,85,89,140],"with":[79],"discontinuous":[81],"global":[82,139],"co-occurrence":[84],"long-distance":[87],"corpus.":[92],"It":[93],"breaks":[94],"shortcomings":[96],"traditional":[98],"that":[101,114,136],"have":[102],"limited":[103],"structure":[104],"only":[107],"learn":[108],"local":[109],"information.":[110],"Experimental":[111],"results":[112],"show":[113],"our":[115],"proposed":[116],"method":[119],"out":[120],"performs":[121],"other":[122],"models":[123],"multiple":[125],"datasets.":[126],"At":[127],"same":[129],"time,":[130],"it":[131],"proved":[133],"through":[134],"experiments":[135],"obtained":[141],"by":[142],"GCN":[143],"supplement":[147],"representation.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
