{"id":"https://openalex.org/W4323020850","doi":"https://doi.org/10.1109/access.2023.3250109","title":"Enhancing Text Classification by Graph Neural Networks With Multi-Granular Topic-Aware Graph","display_name":"Enhancing Text Classification by Graph Neural Networks With Multi-Granular Topic-Aware Graph","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4323020850","doi":"https://doi.org/10.1109/access.2023.3250109"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3250109","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3250109","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10054405.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10054405.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055875522","display_name":"Yongchun Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210086059","display_name":"Sichuan University of Arts and Science","ror":"https://ror.org/00erq7915","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210086059"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yongchun Gu","raw_affiliation_strings":["School of Mathematics, Sichuan University of Arts and Sciences, Dazhou, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics, Sichuan University of Arts and Sciences, Dazhou, China","institution_ids":["https://openalex.org/I4210086059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100364982","display_name":"Yi Wang","orcid":"https://orcid.org/0000-0002-8448-8570"},"institutions":[{"id":"https://openalex.org/I135237710","display_name":"Zhejiang Normal University","ror":"https://ror.org/01vevwk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I135237710"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Wang","raw_affiliation_strings":["Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China","institution_ids":["https://openalex.org/I135237710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040889569","display_name":"Heng\u2010Ru Zhang","orcid":"https://orcid.org/0000-0001-9187-9847"},"institutions":[{"id":"https://openalex.org/I165745306","display_name":"Southwest Petroleum University","ror":"https://ror.org/03h17x602","country_code":"CN","type":"education","lineage":["https://openalex.org/I165745306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng-Ru Zhang","raw_affiliation_strings":["School of Computer Science, Southwest Petroleum University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Southwest Petroleum University, Chengdu, China","institution_ids":["https://openalex.org/I165745306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058422739","display_name":"Jiao Wu","orcid":"https://orcid.org/0000-0003-3181-0674"},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiao Wu","raw_affiliation_strings":["College of Science, China Jiliang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Science, China Jiliang University, Hangzhou, China","institution_ids":["https://openalex.org/I55538621"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069529712","display_name":"GU Xing-quan","orcid":null},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingquan Gu","raw_affiliation_strings":["College of Standardization, China Jiliang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Standardization, China Jiliang University, Hangzhou, China","institution_ids":["https://openalex.org/I55538621"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5055875522"],"corresponding_institution_ids":["https://openalex.org/I4210086059"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":5.2739,"has_fulltext":true,"cited_by_count":30,"citation_normalized_percentile":{"value":0.96454544,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"11","issue":null,"first_page":"20169","last_page":"20183"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9994999766349792,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9993000030517578,"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":0.8459222912788391},{"id":"https://openalex.org/keywords/polysemy","display_name":"Polysemy","score":0.7299397587776184},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5666506886482239},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48157238960266113},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4734199643135071},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.45556971430778503},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4492000937461853},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43379899859428406},{"id":"https://openalex.org/keywords/text-graph","display_name":"Text graph","score":0.4234652519226074},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.41630297899246216},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.21645987033843994},{"id":"https://openalex.org/keywords/text-mining","display_name":"Text mining","score":0.21355587244033813}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8459222912788391},{"id":"https://openalex.org/C2780276568","wikidata":"https://www.wikidata.org/wiki/Q191928","display_name":"Polysemy","level":2,"score":0.7299397587776184},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5666506886482239},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48157238960266113},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4734199643135071},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.45556971430778503},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4492000937461853},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43379899859428406},{"id":"https://openalex.org/C66945725","wikidata":"https://www.wikidata.org/wiki/Q18388823","display_name":"Text graph","level":3,"score":0.4234652519226074},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.41630297899246216},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.21645987033843994},{"id":"https://openalex.org/C71472368","wikidata":"https://www.wikidata.org/wiki/Q676880","display_name":"Text mining","level":2,"score":0.21355587244033813},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3250109","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3250109","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10054405.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:74f558e642524125888d23a6b6303068","is_oa":true,"landing_page_url":"https://doaj.org/article/74f558e642524125888d23a6b6303068","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 20169-20183 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3250109","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3250109","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10054405.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5099999904632568}],"awards":[{"id":"https://openalex.org/G1857103015","display_name":null,"funder_award_id":"2022QD68","funder_id":"https://openalex.org/F4320322990","funder_display_name":"Sichuan University"},{"id":"https://openalex.org/G5308965530","display_name":null,"funder_award_id":"jykf22004","funder_id":"https://openalex.org/F4320322819","funder_display_name":"Zhejiang Normal University"},{"id":"https://openalex.org/G8593680436","display_name":null,"funder_award_id":"11701540","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322819","display_name":"Zhejiang Normal University","ror":"https://ror.org/01vevwk45"},{"id":"https://openalex.org/F4320322990","display_name":"Sichuan University","ror":"https://ror.org/011ashp19"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4323020850.pdf","grobid_xml":"https://content.openalex.org/works/W4323020850.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W1965667542","https://openalex.org/W2132885068","https://openalex.org/W2149684865","https://openalex.org/W2159637323","https://openalex.org/W2265846598","https://openalex.org/W2406273144","https://openalex.org/W2519887557","https://openalex.org/W2889544455","https://openalex.org/W2891369851","https://openalex.org/W2891488835","https://openalex.org/W2902435881","https://openalex.org/W2909182718","https://openalex.org/W2937423263","https://openalex.org/W2943026016","https://openalex.org/W2944500953","https://openalex.org/W2962946486","https://openalex.org/W2963626623","https://openalex.org/W2963912736","https://openalex.org/W2964301648","https://openalex.org/W2970127247","https://openalex.org/W2997162759","https://openalex.org/W2998057994","https://openalex.org/W3006998941","https://openalex.org/W3028860567","https://openalex.org/W3037809848","https://openalex.org/W3090612586","https://openalex.org/W3094758902","https://openalex.org/W3105625590","https://openalex.org/W3110846182","https://openalex.org/W3128465392","https://openalex.org/W3163841364","https://openalex.org/W3166230972","https://openalex.org/W3184110467","https://openalex.org/W3190730109","https://openalex.org/W4285818445","https://openalex.org/W4297499129","https://openalex.org/W6631190155","https://openalex.org/W6682839988","https://openalex.org/W6685053522","https://openalex.org/W6713582272","https://openalex.org/W6720006811","https://openalex.org/W6760001035"],"related_works":["https://openalex.org/W2376040010","https://openalex.org/W2613880225","https://openalex.org/W2788559978","https://openalex.org/W2358036664","https://openalex.org/W2891304714","https://openalex.org/W4385239993","https://openalex.org/W2310152915","https://openalex.org/W2362895247","https://openalex.org/W4285531126","https://openalex.org/W4285119675"],"abstract_inverted_index":{"Text":[0],"classification":[1,86,100],"based":[2,40,102],"on":[3,30,41,103,133,189],"graph":[4,136],"neural":[5],"networks":[6],"(GNNs)":[7],"has":[8,147],"been":[9],"widely":[10],"studied":[11],"by":[12,91,182],"virtue":[13],"of":[14,25,75,84,124,144,158,178],"its":[15],"potential":[16],"to":[17,43,110,118,154,166,174],"capture":[18,44],"complex":[19],"and":[20,55,128,161],"across-granularity":[21],"relations":[22,130],"among":[23,49],"texts":[24],"different":[26,76],"types":[27],"from":[28,105],"learning":[29],"a":[31,59,97,120,134],"text":[32,38,85,99,135],"graph.":[33],"Existing":[34],"methods":[35],"typically":[36],"construct":[37],"graphs":[39],"words-documents":[42,56],"relevant":[45],"intra-class":[46],"document":[47],"representations":[48],"the":[50,156,176],"same":[51],"documents":[52,67,74],"via":[53],"words-words":[54],"propagation.":[57,81],"However,":[58],"natural":[60],"problem":[61],"is":[62,153,165,173],"that":[63,195],"polysemy":[64,183],"words":[65],"in":[66],"may":[68],"become":[69],"an":[70],"information":[71,80,180],"medium":[72],"between":[73],"categories,":[77],"promoting":[78],"heterophily":[79,179],"The":[82,142,151,163,171],"performance":[83],"will":[87],"be":[88],"somewhat":[89],"constrained":[90],"this":[92,138],"issue.":[93],"This":[94],"paper":[95],"proposes":[96],"novel":[98],"method":[101,198],"GNN":[104],"multi-granular":[106],"topic-aware":[107],"perspective,":[108],"referred":[109],"as":[111],"Text-MGNN.":[112],"Specifically,":[113],"topic":[114,145],"nodes":[115,146],"are":[116,131,187],"introduced":[117],"build":[119],"triple":[121,139],"node":[122,140],"set":[123],"\u201cword,":[125],"document,":[126],"topic,\u201d":[127],"multi-granularity":[129],"modeled":[132],"for":[137],"set.":[141],"introduction":[143],"three":[148,190],"significant":[149],"advantages.":[150],"first":[152],"strengthen":[155],"propagation":[157],"topics,":[159],"words,":[160],"documents.":[162],"second":[164],"enhance":[167],"class-aware":[168],"representation":[169],"learning.":[170],"final":[172],"mitigate":[175],"effect":[177],"caused":[181],"words.":[184],"Extensive":[185],"experiments":[186],"conducted":[188],"real-world":[191],"datasets.":[192],"Results":[193],"validate":[194],"our":[196],"proposed":[197],"outperforms":[199],"11":[200],"baselines":[201],"methods.":[202]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":8}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}