{"id":"https://openalex.org/W4394579259","doi":"https://doi.org/10.1007/s11063-024-11595-z","title":"DialGNN: Heterogeneous Graph Neural Networks for Dialogue Classification","display_name":"DialGNN: Heterogeneous Graph Neural Networks for Dialogue Classification","publication_year":2024,"publication_date":"2024-04-08","ids":{"openalex":"https://openalex.org/W4394579259","doi":"https://doi.org/10.1007/s11063-024-11595-z"},"language":"en","primary_location":{"id":"doi:10.1007/s11063-024-11595-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-024-11595-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11595-z.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11595-z.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100395042","display_name":"Yan Yan","orcid":"https://orcid.org/0000-0002-0187-7010"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Yan","raw_affiliation_strings":["Department of Artificial Intelligence, China University of Mining and Technology, Beijing, 100083, China"],"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, China University of Mining and Technology, Beijing, 100083, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100385138","display_name":"Bowen Zhang","orcid":"https://orcid.org/0000-0002-3581-9476"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bo-Wen Zhang","raw_affiliation_strings":["Beijing Academy of Artificial Intelligence, Beijing, 100084, China"],"affiliations":[{"raw_affiliation_string":"Beijing Academy of Artificial Intelligence, Beijing, 100084, China","institution_ids":["https://openalex.org/I4210100255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108918144","display_name":"Peng-hao Min","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng-hao Min","raw_affiliation_strings":["Department of Artificial Intelligence, China University of Mining and Technology, Beijing, 100083, China"],"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, China University of Mining and Technology, Beijing, 100083, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114067872","display_name":"Guan-wen Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guan-wen Ding","raw_affiliation_strings":["Department of Artificial Intelligence, China University of Mining and Technology, Beijing, 100083, China"],"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, China University of Mining and Technology, Beijing, 100083, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036080383","display_name":"Jun-yuan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun-yuan Liu","raw_affiliation_strings":["Department of Artificial Intelligence, China University of Mining and Technology, Beijing, 100083, China"],"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, China University of Mining and Technology, Beijing, 100083, China","institution_ids":["https://openalex.org/I25757504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100385138"],"corresponding_institution_ids":["https://openalex.org/I4210100255"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":1.0034,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.78708342,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"56","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9995999932289124,"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":0.9995999932289124,"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/T12031","display_name":"Speech and dialogue systems","score":0.9972000122070312,"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":0.9947999715805054,"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":0.6235899925231934},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5650938749313354},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48571571707725525},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45785272121429443},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.23681065440177917}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6235899925231934},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5650938749313354},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48571571707725525},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45785272121429443},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.23681065440177917}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11063-024-11595-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-024-11595-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11595-z.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11063-024-11595-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-024-11595-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11595-z.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6499999761581421,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G3792021300","display_name":null,"funder_award_id":"2023ZKPYJD06","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G7598525383","display_name":null,"funder_award_id":"G2022123009L","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4394579259.pdf"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W2321588627","https://openalex.org/W2470673105","https://openalex.org/W2514588627","https://openalex.org/W2517194566","https://openalex.org/W2891533927","https://openalex.org/W2954500018","https://openalex.org/W2962946486","https://openalex.org/W2963765493","https://openalex.org/W2985882473","https://openalex.org/W2991537901","https://openalex.org/W2997075693","https://openalex.org/W2997174602","https://openalex.org/W2997200074","https://openalex.org/W3013860672","https://openalex.org/W3116705004","https://openalex.org/W3175552668","https://openalex.org/W3209855825","https://openalex.org/W4200609346","https://openalex.org/W4205422455","https://openalex.org/W4293686623","https://openalex.org/W4312410594","https://openalex.org/W4312952234","https://openalex.org/W4322761487","https://openalex.org/W4327652415","https://openalex.org/W6600424091"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2350741829"],"abstract_inverted_index":{"Abstract":[0],"Dialogue":[1],"systems":[2],"have":[3],"attracted":[4,41],"growing":[5],"research":[6,18],"interests":[7],"due":[8],"to":[9,25],"its":[10,100],"widespread":[11],"applications":[12],"in":[13,29,78,130],"various":[14,91],"domains.":[15],"However,":[16],"most":[17],"work":[19],"focus":[20],"on":[21,112],"sentence-level":[22],"intent":[23],"recognition":[24],"interpret":[26],"user":[27],"utterances":[28],"dialogue":[30,61,67,137],"systems,":[31],"while":[32],"the":[33,36,58,65,121,133],"comprehension":[34],"of":[35,60,81,90,135,141],"whole":[37],"documents":[38],"has":[39],"not":[40],"sufficient":[42],"attention.":[43],"In":[44],"this":[45],"paper,":[46],"we":[47],"propose":[48],"DialGNN,":[49],"a":[50,71,127],"heterogeneous":[51,72],"graph":[52,73,85],"neural":[53],"network":[54],"framework":[55,86],"tailored":[56],"for":[57],"problem":[59],"classification":[62,134],"which":[63,102,117],"takes":[64],"entire":[66],"as":[68,97],"input.":[69],"Specifically,":[70,123],"is":[74],"constructed":[75],"with":[76,105],"nodes":[77],"different":[79],"levels":[80],"semantic":[82],"granularity.":[83],"The":[84,139],"allows":[87],"flexible":[88],"integration":[89],"pre-trained":[92],"language":[93],"representation":[94],"models,":[95],"such":[96],"BERT":[98],"and":[99,114,120,143],"variants,":[101],"endows":[103],"DialGNN":[104,110,142],"powerful":[106],"text":[107],"representational":[108],"capabilities.":[109],"outperforms":[111],"CM":[113],"ECS":[115],"datasets,":[116],"demonstrates":[118],"robustness":[119],"effectiveness.":[122],"our":[124],"model":[125],"achieves":[126],"notable":[128],"enhancement":[129],"performance,":[131],"optimizing":[132],"document-level":[136],"text.":[138],"implementation":[140],"related":[144],"data":[145],"are":[146],"shared":[147],"through":[148],"https://github.com/821code/DialGNN":[149],".":[150]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}