{"id":"https://openalex.org/W4200095136","doi":"https://doi.org/10.1145/3487075.3487162","title":"A Dual-branch Graph Convolutional Network on Imbalanced Node Classification","display_name":"A Dual-branch Graph Convolutional Network on Imbalanced Node Classification","publication_year":2021,"publication_date":"2021-10-19","ids":{"openalex":"https://openalex.org/W4200095136","doi":"https://doi.org/10.1145/3487075.3487162"},"language":"en","primary_location":{"id":"doi:10.1145/3487075.3487162","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3487075.3487162","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","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/A5108016571","display_name":"Xiaoguo Wang","orcid":"https://orcid.org/0009-0006-0528-5684"},"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":true,"raw_author_name":"Xiaoguo Wang","raw_affiliation_strings":["College of Electronics and Information Engineering, Tongji University, China"],"affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Tongji University, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100459749","display_name":"Jiali Chen","orcid":"https://orcid.org/0000-0001-8064-1577"},"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":"Jiali Chen","raw_affiliation_strings":["College of Electronics and Information Engineering, Tongji University, China"],"affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Tongji University, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5108016571"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57237499,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","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/T11273","display_name":"Advanced Graph Neural Networks","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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9605000019073486,"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":0.9473999738693237,"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":0.7479282021522522},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6495310664176941},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.6203345656394958},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.49510684609413147},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4672313332557678},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.45624321699142456},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.4400763213634491},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3558507561683655},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32038360834121704}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7479282021522522},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6495310664176941},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.6203345656394958},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.49510684609413147},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4672313332557678},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.45624321699142456},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.4400763213634491},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3558507561683655},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32038360834121704},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3487075.3487162","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3487075.3487162","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6100000143051147}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1602136775","https://openalex.org/W1662382123","https://openalex.org/W2088252378","https://openalex.org/W2519887557","https://openalex.org/W2624431344","https://openalex.org/W2807021761","https://openalex.org/W2807842095","https://openalex.org/W2887167794","https://openalex.org/W2908461307","https://openalex.org/W2911286998","https://openalex.org/W2912083425","https://openalex.org/W2963555845","https://openalex.org/W2964015378","https://openalex.org/W2996268457","https://openalex.org/W3011124515","https://openalex.org/W3035286001","https://openalex.org/W3100848837","https://openalex.org/W3115443211","https://openalex.org/W3134509497","https://openalex.org/W3153131045","https://openalex.org/W3209047863","https://openalex.org/W4213069590","https://openalex.org/W4297733535","https://openalex.org/W6739901393","https://openalex.org/W6779961489","https://openalex.org/W6785081404","https://openalex.org/W6794020371"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4313906399","https://openalex.org/W4321487865","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W2318112981","https://openalex.org/W4312417841","https://openalex.org/W4225147082","https://openalex.org/W2778653980"],"abstract_inverted_index":{"Graph":[0,69],"convolutional":[1],"neural":[2],"networks":[3],"(GCNs)":[4],"have":[5],"attracted":[6],"much":[7],"attention":[8],"in":[9,136],"dealing":[10],"with":[11],"various":[12],"node":[13,20,56,139],"classification":[14,21,57,119,140],"tasks":[15,22],"on":[16,59,83,126],"graphs.":[17],"Some":[18],"real-world":[19],"face":[23],"the":[24,27,52,77,87,101,105,109,118],"situation":[25],"that":[26,37,131],"number":[28],"of":[29,38,54,80,90,103,107,121],"minority":[30,110,122],"class":[31,40,82,111,115,123],"nodes":[32,112],"is":[33],"significantly":[34],"less":[35],"than":[36],"majority":[39,81,114],"nodes.":[41,124],"This":[42,98],"makes":[43],"us":[44],"more":[45],"concerned":[46],"about":[47],"how":[48],"to":[49],"effectively":[50],"solve":[51,62],"problem":[53],"imbalanced":[55,138],"based":[58],"GCNs.":[60],"To":[61],"this":[63],"problem,":[64],"we":[65],"propose":[66],"a":[67],"Dual-branch":[68],"Convolutional":[70],"Network":[71],"framework":[72,99],"(D-GCN),":[73],"which":[74],"can":[75],"reduce":[76],"dominant":[78],"effect":[79],"topology":[84],"aggregation":[85],"and":[86,116],"negative":[88],"impact":[89],"information":[91],"differences":[92],"caused":[93],"by":[94],"graph":[95,128],"structure":[96],"reconstruction.":[97],"achieves":[100],"goal":[102],"decreasing":[104],"possibility":[106],"misrecognizing":[108],"as":[113],"improving":[117],"performance":[120],"Experiments":[125],"several":[127],"datasets":[129],"demonstrate":[130],"D-GCN":[132],"outperforms":[133],"representative":[134],"baselines":[135],"solving":[137],"tasks.":[141]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}