{"id":"https://openalex.org/W2979086518","doi":"https://doi.org/10.1109/ijcnn.2019.8851698","title":"DAGCN: Dual Attention Graph Convolutional Networks","display_name":"DAGCN: Dual Attention Graph Convolutional Networks","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2979086518","doi":"https://doi.org/10.1109/ijcnn.2019.8851698","mag":"2979086518"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8851698","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851698","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","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/A5028402625","display_name":"Fengwen Chen","orcid":"https://orcid.org/0000-0002-7852-4504"},"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":true,"raw_author_name":"Fengwen Chen","raw_affiliation_strings":["Centre for Artificial Intelligence, FEIT, University of Technology, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"Centre for Artificial Intelligence, FEIT, University of Technology, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008056593","display_name":"Shirui Pan","orcid":"https://orcid.org/0000-0003-0794-527X"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shirui Pan","raw_affiliation_strings":["Faculty of Information Technology, Monash University, Australia"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Monash University, Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057139422","display_name":"Jing Jiang","orcid":"https://orcid.org/0000-0001-5301-7779"},"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":"Jing Jiang","raw_affiliation_strings":["Centre for Artificial Intelligence, FEIT, University of Technology, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"Centre for Artificial Intelligence, FEIT, University of Technology, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102878677","display_name":"Huan Huo","orcid":"https://orcid.org/0000-0003-2440-714X"},"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":"Huan Huo","raw_affiliation_strings":["School of software, FEIT, University of Technology, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"School of software, FEIT, University of Technology, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059227406","display_name":"Guodong Long","orcid":"https://orcid.org/0000-0003-3740-9515"},"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":"Guodong Long","raw_affiliation_strings":["Centre for Artificial Intelligence, FEIT, University of Technology, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"Centre for Artificial Intelligence, FEIT, University of Technology, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5028402625"],"corresponding_institution_ids":["https://openalex.org/I114017466"],"apc_list":null,"apc_paid":null,"fwci":5.3207,"has_fulltext":false,"cited_by_count":63,"citation_normalized_percentile":{"value":0.96523437,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":1.0,"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/T11273","display_name":"Advanced Graph Neural Networks","score":1.0,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9905999898910522,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9836999773979187,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7628517150878906},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.7394951581954956},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5665621757507324},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5298411846160889},{"id":"https://openalex.org/keywords/topological-graph-theory","display_name":"Topological graph theory","score":0.43278244137763977},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38337230682373047},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3401959538459778},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.24733084440231323},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.24073711037635803}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7628517150878906},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.7394951581954956},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5665621757507324},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5298411846160889},{"id":"https://openalex.org/C157406716","wikidata":"https://www.wikidata.org/wiki/Q4115842","display_name":"Topological graph theory","level":5,"score":0.43278244137763977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38337230682373047},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3401959538459778},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.24733084440231323},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.24073711037635803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8851698","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851698","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320315885","display_name":"Australian Government","ror":"https://ror.org/0314h5y94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":80,"referenced_works":["https://openalex.org/W637153065","https://openalex.org/W1501856433","https://openalex.org/W1522301498","https://openalex.org/W1662382123","https://openalex.org/W1816257748","https://openalex.org/W1981380913","https://openalex.org/W2008857988","https://openalex.org/W2032280284","https://openalex.org/W2107793528","https://openalex.org/W2119821739","https://openalex.org/W2127827747","https://openalex.org/W2133564696","https://openalex.org/W2142498761","https://openalex.org/W2147286743","https://openalex.org/W2158990373","https://openalex.org/W2159156271","https://openalex.org/W2161984370","https://openalex.org/W2194775991","https://openalex.org/W2439554109","https://openalex.org/W2465015709","https://openalex.org/W2519887557","https://openalex.org/W2574817444","https://openalex.org/W2597655663","https://openalex.org/W2610153490","https://openalex.org/W2788919350","https://openalex.org/W2803471865","https://openalex.org/W2803881248","https://openalex.org/W2808409763","https://openalex.org/W2809343047","https://openalex.org/W2890855364","https://openalex.org/W2911738047","https://openalex.org/W2950898568","https://openalex.org/W2952402334","https://openalex.org/W2962767366","https://openalex.org/W2963017945","https://openalex.org/W2963043672","https://openalex.org/W2963084622","https://openalex.org/W2963280944","https://openalex.org/W2963358464","https://openalex.org/W2963858333","https://openalex.org/W2963984147","https://openalex.org/W2964015378","https://openalex.org/W2964065761","https://openalex.org/W2964113829","https://openalex.org/W2964121744","https://openalex.org/W2964145825","https://openalex.org/W2964189376","https://openalex.org/W2964308564","https://openalex.org/W2964311892","https://openalex.org/W2964321699","https://openalex.org/W4210257598","https://openalex.org/W4239510810","https://openalex.org/W4294558607","https://openalex.org/W4297733535","https://openalex.org/W6620673361","https://openalex.org/W6631190155","https://openalex.org/W6637178625","https://openalex.org/W6679434410","https://openalex.org/W6681029592","https://openalex.org/W6685350579","https://openalex.org/W6690815549","https://openalex.org/W6713582119","https://openalex.org/W6719270105","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6731976766","https://openalex.org/W6735377749","https://openalex.org/W6737558694","https://openalex.org/W6738626670","https://openalex.org/W6738964360","https://openalex.org/W6744649695","https://openalex.org/W6745537798","https://openalex.org/W6746015598","https://openalex.org/W6747954111","https://openalex.org/W6748524405","https://openalex.org/W6751570989","https://openalex.org/W6751943552","https://openalex.org/W6758327135","https://openalex.org/W6807384801","https://openalex.org/W7065437122"],"related_works":["https://openalex.org/W3015684221","https://openalex.org/W3190454392","https://openalex.org/W4205991736","https://openalex.org/W2767597557","https://openalex.org/W3094552683","https://openalex.org/W3211302945","https://openalex.org/W4284975088","https://openalex.org/W4386136067","https://openalex.org/W4366772049","https://openalex.org/W4388486485"],"abstract_inverted_index":{"Graph":[0],"convolutional":[1,143],"networks":[2,23,144],"(GCNs)":[3],"have":[4,77],"recently":[5],"become":[6],"one":[7],"of":[8,48,101,123,155,187,238],"the":[9,38,45,72,81,87,107,121,127,153,180,184,203],"most":[10],"powerful":[11],"tools":[12],"for":[13,71,95,202],"graph":[14,69,82,108,142,164,181,190,204,213],"analytics":[15],"tasks":[16],"in":[17,80,198],"numerous":[18],"applications,":[19],"ranging":[20],"from":[21,183],"social":[22],"and":[24,30,59,126,167,215],"natural":[25],"language":[26],"processing":[27],"to":[28,33,36,55,67,146,178],"bioinformatics":[29],"chemoinformatics,":[31],"thanks":[32],"their":[34],"ability":[35],"capture":[37],"complex":[39],"relationships":[40],"between":[41,129],"concepts.":[42],"At":[43],"present,":[44],"vast":[46],"majority":[47],"GCNs":[49],"use":[50],"a":[51,57,64,98,136,161,170,174,188,235],"neighborhood":[52,96],"aggregation":[53],"framework":[54,138,226],"learn":[56],"continuous":[58],"compact":[60],"vector,":[61],"then":[62,168],"performing":[63],"pooling":[65,114,117,176],"operation":[66],"generalize":[68,179],"embedding":[70],"classification":[73,83,205],"task.":[74,206],"These":[75],"approaches":[76],"two":[78],"disadvantages":[79],"task:":[84],"(1)when":[85],"only":[86,228],"largest":[88],"sub-graph":[89],"structure":[90],"(k-hop":[91],"neighbor)":[92],"is":[93,104,196],"used":[94],"aggregation,":[97],"large":[99],"amount":[100],"early-stage":[102],"information":[103],"lost":[105],"during":[106],"convolution":[109,165],"step;":[110],"(2)":[111],"simple":[112],"average/sum":[113],"or":[115],"max":[116],"utilized,":[118],"which":[119],"loses":[120],"characteristics":[122],"each":[124],"node":[125],"topology":[128],"nodes.":[130],"In":[131],"this":[132],"paper,":[133],"we":[134],"propose":[135],"novel":[137,162],"called,":[139],"dual":[140,193],"attention":[141,163,172,194],"(DAGCN)":[145],"address":[147],"these":[148],"problems.":[149],"DAGCN":[150],"automatically":[151],"learns":[152],"importance":[154],"neighbors":[156],"at":[157],"different":[158],"hops":[159],"using":[160],"layer,":[166,177],"employs":[169],"second":[171],"component,":[173],"self-attention":[175],"representation":[182],"various":[185],"aspects":[186],"matrix":[189],"embedding.":[191],"The":[192,220],"network":[195],"trained":[197],"an":[199],"end-to-end":[200],"manner":[201],"We":[207],"compare":[208],"our":[209,225],"model":[210],"with":[211],"state-of-the-art":[212],"kernels":[214],"other":[216,230],"deep":[217],"learning":[218],"methods.":[219],"experimental":[221],"results":[222],"show":[223],"that":[224],"not":[227],"outperforms":[229],"baselines":[231],"but":[232],"also":[233],"achieves":[234],"better":[236],"rate":[237],"convergence.":[239]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
