{"id":"https://openalex.org/W4403600694","doi":"https://doi.org/10.1109/tcss.2024.3468890","title":"Adapting GNNs for Document Understanding: A\u00a0Flexible Framework With Multiview Global\u00a0Graphs","display_name":"Adapting GNNs for Document Understanding: A\u00a0Flexible Framework With Multiview Global\u00a0Graphs","publication_year":2024,"publication_date":"2024-10-21","ids":{"openalex":"https://openalex.org/W4403600694","doi":"https://doi.org/10.1109/tcss.2024.3468890"},"language":"en","primary_location":{"id":"doi:10.1109/tcss.2024.3468890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2024.3468890","pdf_url":null,"source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Computational Social 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/A5114166660","display_name":"Ze Wu","orcid":"https://orcid.org/0000-0002-5353-1943"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuojia Wu","raw_affiliation_strings":["Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-5353-1943","affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100784844","display_name":"Qi Zhang","orcid":"https://orcid.org/0000-0002-1037-1361"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Zhang","raw_affiliation_strings":["Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-1037-1361","affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024791074","display_name":"Duoqian Miao","orcid":"https://orcid.org/0000-0001-6588-1468"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Duoqian Miao","raw_affiliation_strings":["Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-6588-1468","affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091807986","display_name":"Xuerong Zhao","orcid":"https://orcid.org/0000-0002-2324-955X"},"institutions":[{"id":"https://openalex.org/I21945476","display_name":"Shanghai Normal University","ror":"https://ror.org/01cxqmw89","country_code":"CN","type":"education","lineage":["https://openalex.org/I21945476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuerong Zhao","raw_affiliation_strings":["Shanghai Normal University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-2324-955X","affiliations":[{"raw_affiliation_string":"Shanghai Normal University, Shanghai, China","institution_ids":["https://openalex.org/I21945476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034376285","display_name":"Kaize Shi","orcid":"https://orcid.org/0000-0003-3561-3627"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Kaize Shi","raw_affiliation_strings":["Data Science and Machine Intelligence Laboratory, University of Technology Sydney, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0003-3561-3627","affiliations":[{"raw_affiliation_string":"Data Science and Machine Intelligence Laboratory, University of Technology Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8335,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.78014096,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"12","issue":"2","first_page":"608","last_page":"621"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9847000241279602,"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":0.9847000241279602,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.978600025177002,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9424999952316284,"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":0.5865815877914429},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3652327060699463}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5865815877914429},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3652327060699463}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcss.2024.3468890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2024.3468890","pdf_url":null,"source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Computational Social Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W2019759670","https://openalex.org/W2035299679","https://openalex.org/W2064675550","https://openalex.org/W2072596762","https://openalex.org/W2113378307","https://openalex.org/W2159397589","https://openalex.org/W2250539671","https://openalex.org/W2626685773","https://openalex.org/W2896337548","https://openalex.org/W2896457183","https://openalex.org/W2951457034","https://openalex.org/W2962946486","https://openalex.org/W2963626623","https://openalex.org/W2964301648","https://openalex.org/W2970183009","https://openalex.org/W2970398671","https://openalex.org/W2997162759","https://openalex.org/W2998496395","https://openalex.org/W2999786665","https://openalex.org/W3035568641","https://openalex.org/W3106229813","https://openalex.org/W3117136530","https://openalex.org/W3124806699","https://openalex.org/W3171978172","https://openalex.org/W3173753074","https://openalex.org/W3213097325","https://openalex.org/W3213938648","https://openalex.org/W4210466371","https://openalex.org/W4221101570","https://openalex.org/W4226283934","https://openalex.org/W4280582438","https://openalex.org/W4285135404","https://openalex.org/W4285307786","https://openalex.org/W4319264941","https://openalex.org/W4377709558","https://openalex.org/W4382202724","https://openalex.org/W4385245566","https://openalex.org/W4385488904","https://openalex.org/W4393032946","https://openalex.org/W4393160040","https://openalex.org/W4394769991","https://openalex.org/W4396734757","https://openalex.org/W4400033057","https://openalex.org/W4401023623","https://openalex.org/W4403780602","https://openalex.org/W6636510571","https://openalex.org/W6639619044","https://openalex.org/W6679775712","https://openalex.org/W6713582272","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6760001035","https://openalex.org/W6766673545","https://openalex.org/W6779674571","https://openalex.org/W6859577862"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Graph":[0],"neural":[1],"networks":[2],"(GNNs)":[3],"have":[4],"recently":[5],"gained":[6],"attention":[7],"for":[8,168,227],"capturing":[9],"complex":[10],"relations,":[11],"prompting":[12],"researchers":[13],"to":[14,67,185],"explore":[15],"their":[16],"potential":[17],"in":[18,49],"document":[19,103,117,141,155],"classification.":[20],"Existing":[21],"studies":[22],"serving":[23],"this":[24,96,158],"purpose":[25],"fall":[26],"into":[27,154],"two":[28],"directions:":[29],"inductive":[30],"learning":[31,41,75,88,105,121,166],"focusing":[32,119],"on":[33,120],"personalized":[34,151],"context":[35,152],"relations":[36,46,153],"within":[37,89],"documents":[38,48],"and":[39,61,74,85,116,178,212],"transductive":[40],"targeting":[42],"the":[43,68,114,122,137,144,169,174,194,197],"global":[44,86,110,124,171,198,211],"distribution":[45,125],"among":[47],"a":[50,100,133,163],"corpus.":[51],"Both":[52],"directions":[53],"extract":[54],"distinct":[55],"types":[56],"of":[57,70,127,140,147,196],"beneficial":[58],"structural":[59],"information":[60,126],"yield":[62],"encouraging":[63],"outcomes.":[64],"However,":[65],"due":[66],"incompatibility":[69],"underlying":[71],"graph":[72,176],"structures":[73],"settings,":[76],"developing":[77],"an":[78],"enhanced":[79],"model":[80],"that":[81,107,202],"effectively":[82],"integrates":[83],"local":[84,213],"relational":[87,214],"existing":[90],"frameworks":[91],"is":[92],"challenging.":[93],"To":[94],"address":[95],"issue,":[97],"we":[98,161],"propose":[99],"new":[101],"GNN-based":[102,228],"representation":[104,165],"framework":[106,184,204,223],"incorporates":[108],"multiview":[109,170,175],"graphs":[111],"at":[112,129],"both":[113,210],"word":[115,148],"levels,":[118],"diverse":[123],"texts":[128],"different":[130],"granularities.":[131],"Additionally,":[132],"contextual":[134],"encoder":[135],"derives":[136],"initial":[138],"representations":[139,146,156],"nodes":[142],"from":[143],"updated":[145],"nodes,":[149],"integrating":[150,209],"during":[157,188],"process.":[159],"Finally,":[160],"tailor":[162],"node":[164],"strategy":[167],"graphs,":[172],"called":[173],"sampling":[177],"updating":[179],"module,":[180],"which":[181],"allows":[182],"our":[183,203,222],"operate":[186],"efficiently":[187],"training":[189],"without":[190],"being":[191],"constrained":[192],"by":[193,208],"scale":[195],"graph.":[199],"Experiments":[200],"indicate":[201],"generally":[205],"enhances":[206],"performance":[207],"learning.":[215],"When":[216],"combined":[217],"with":[218],"large-scale":[219],"language":[220],"models,":[221],"achieves":[224],"state-of-the-art":[225],"results":[226],"models":[229],"across":[230],"multiple":[231],"datasets.":[232]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
