{"id":"https://openalex.org/W4307720136","doi":"https://doi.org/10.1080/01969722.2022.2137646","title":"An Integrated Graph-of-Words with Tensor Graph Neural Network Learning Paradigm for Text Classification","display_name":"An Integrated Graph-of-Words with Tensor Graph Neural Network Learning Paradigm for Text Classification","publication_year":2022,"publication_date":"2022-10-28","ids":{"openalex":"https://openalex.org/W4307720136","doi":"https://doi.org/10.1080/01969722.2022.2137646"},"language":"en","primary_location":{"id":"doi:10.1080/01969722.2022.2137646","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01969722.2022.2137646","pdf_url":null,"source":{"id":"https://openalex.org/S117436046","display_name":"Cybernetics & Systems","issn_l":"0196-9722","issn":["0196-9722","1087-6553"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybernetics and Systems","raw_type":"journal-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/A5006709815","display_name":"Tham Vo","orcid":"https://orcid.org/0000-0001-7291-4168"},"institutions":[{"id":"https://openalex.org/I4210111957","display_name":"B\u00ecnh D\u01b0\u01a1ng University","ror":"https://ror.org/02b9zqw68","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210111957"]},{"id":"https://openalex.org/I4391012539","display_name":"Thu Dau Mot University","ror":"https://ror.org/010y5b925","country_code":null,"type":"education","lineage":["https://openalex.org/I4391012539"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Tham Vo","raw_affiliation_strings":["Thu Dau Mot University, Binh Duong, Vietnam"],"raw_orcid":"https://orcid.org/0000-0001-7291-4168","affiliations":[{"raw_affiliation_string":"Thu Dau Mot University, Binh Duong, Vietnam","institution_ids":["https://openalex.org/I4210111957","https://openalex.org/I4391012539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069412123","display_name":"Hien Thanh Vu","orcid":null},"institutions":[{"id":"https://openalex.org/I4387155935","display_name":"HUTECH University","ror":"https://ror.org/05xpj2n48","country_code":null,"type":"education","lineage":["https://openalex.org/I4387155935"]},{"id":"https://openalex.org/I47265099","display_name":"Ho Chi Minh City University of Technology","ror":"https://ror.org/04qva2324","country_code":"VN","type":"education","lineage":["https://openalex.org/I123565023","https://openalex.org/I47265099"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Hien Thanh Vu","raw_affiliation_strings":["Faculty of Information Technology, HUTECH University, Ho Chi Minh City, Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, HUTECH University, Ho Chi Minh City, Vietnam","institution_ids":["https://openalex.org/I47265099","https://openalex.org/I4387155935"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006709815"],"corresponding_institution_ids":["https://openalex.org/I4210111957","https://openalex.org/I4391012539"],"apc_list":null,"apc_paid":null,"fwci":0.1387,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.5575914,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"55","issue":"5","first_page":"1255","last_page":"1284"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9987000226974487,"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":0.9940000176429749,"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":0.8159888982772827},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6085383892059326},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6029310822486877},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.586918294429779},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5464034676551819},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4604514241218567},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.44944998621940613},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.42815542221069336},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4207058250904083},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.41497132182121277},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.41118013858795166},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.40342432260513306},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3315609395503998}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8159888982772827},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6085383892059326},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6029310822486877},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.586918294429779},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5464034676551819},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4604514241218567},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.44944998621940613},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.42815542221069336},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4207058250904083},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41497132182121277},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.41118013858795166},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.40342432260513306},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3315609395503998},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/01969722.2022.2137646","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01969722.2022.2137646","pdf_url":null,"source":{"id":"https://openalex.org/S117436046","display_name":"Cybernetics & Systems","issn_l":"0196-9722","issn":["0196-9722","1087-6553"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybernetics and Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W49342364","https://openalex.org/W1506025786","https://openalex.org/W1826790618","https://openalex.org/W2048137247","https://openalex.org/W2123442489","https://openalex.org/W2250539671","https://openalex.org/W2250662230","https://openalex.org/W2265846598","https://openalex.org/W2417677256","https://openalex.org/W2586131832","https://openalex.org/W2610202954","https://openalex.org/W2739996966","https://openalex.org/W2788667846","https://openalex.org/W2789655955","https://openalex.org/W2804934982","https://openalex.org/W2808133401","https://openalex.org/W2891488835","https://openalex.org/W2911514212","https://openalex.org/W2914767245","https://openalex.org/W2937423263","https://openalex.org/W2962739339","https://openalex.org/W2962946486","https://openalex.org/W2963026768","https://openalex.org/W2963224980","https://openalex.org/W2963355447","https://openalex.org/W2964222246","https://openalex.org/W2997162759","https://openalex.org/W2998009309","https://openalex.org/W3105625590","https://openalex.org/W3135143565","https://openalex.org/W3156333129"],"related_works":["https://openalex.org/W4311257506","https://openalex.org/W2337926734","https://openalex.org/W4366224123","https://openalex.org/W2963958939","https://openalex.org/W4320802194","https://openalex.org/W4323060038","https://openalex.org/W2914959431","https://openalex.org/W3173182854","https://openalex.org/W4299822940","https://openalex.org/W4315777907"],"abstract_inverted_index":{"In":[0,103,142],"recent":[1,62,157],"years,":[2],"with":[3,49,75,156],"tremendous":[4],"progresses":[5],"of":[6,57,61,80,101,149,179],"deep":[7],"learning":[8,120,161],"in":[9,109,154,167,183],"multiple":[10],"disciplines,":[11],"there":[12,32],"are":[13,33,90],"several":[14,34],"advanced":[15],"sequential":[16,78,133],"neural-network":[17],"(NN)":[18],"based":[19],"architectures":[20,37],"(e.g.,":[21],"recurrent":[22],"neural":[23],"network\u2014RNN,":[24],"Auto-Encoding\u2014AE,":[25],"transformer,":[26],"etc.)":[27],"have":[28,44],"been":[29,45],"proposed.":[30],"Recently,":[31],"well-known":[35],"GNN-based":[36,64],"like":[38],"as":[39,93],"graph":[40,118,138],"convolutional":[41,139],"network":[42,140],"(GNN)":[43],"proposed":[46,63,113,126,151,181],"to":[47,52,70,95,105,144],"deal":[48],"challenges":[50],"related":[51],"the":[53,72,76,83,97,137,147,175],"global":[54,73],"representation":[55,119,135,160],"preservation":[56],"text.":[58],"However,":[59],"most":[60],"text-embedding":[65],"models":[66],"still":[67],"be":[68],"unable":[69,94],"integrate":[71],"structure":[74],"semantic":[77,131],"representations":[79,100],"words/sentences":[81],"into":[82],"unified":[84],"textual":[85,134,169],"embedding":[86],"space.":[87],"Moreover,":[88],"they":[89],"also":[91],"considered":[92],"learn":[96],"rich":[98],"context-varied":[99],"words.":[102],"order":[104,143],"tackle":[106],"aforementioned":[107],"challenges,":[108],"this":[110,184],"paper":[111],"we":[112,163],"a":[114],"novel":[115],"integrated":[116,130],"text":[117,159],"approach,":[121],"named":[122],"as:":[123],"GOWSeqGCN.":[124],"Our":[125],"GOWSeqGCN":[127,152],"is":[128],"an":[129],"graph-of-words":[132],"under":[136],"framework.":[141],"demonstrate":[145],"for":[146],"effectiveness":[148],"our":[150,180],"model":[153],"comparing":[155],"state-of-the-art":[158],"baselines,":[162],"conducted":[164],"extensive":[165],"experiments":[166],"benchmark":[168],"datasets.":[170],"The":[171],"experimental":[172],"outputs":[173],"showed":[174],"outperformances":[176],"and":[177],"necessary":[178],"ideas":[182],"paper.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
