{"id":"https://openalex.org/W3191845507","doi":"https://doi.org/10.24963/ijcai.2021/210","title":"Node-wise Localization of Graph Neural Networks","display_name":"Node-wise Localization of Graph Neural Networks","publication_year":2021,"publication_date":"2021-08-01","ids":{"openalex":"https://openalex.org/W3191845507","doi":"https://doi.org/10.24963/ijcai.2021/210","mag":"3191845507"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2021/210","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/210","pdf_url":"https://www.ijcai.org/proceedings/2021/0210.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2021/0210.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zemin Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I79891267","display_name":"Singapore Management University","ror":"https://ror.org/050qmg959","country_code":"SG","type":"education","lineage":["https://openalex.org/I79891267"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zemin Liu","raw_affiliation_strings":["Singapore Management University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Singapore Management University, Singapore","institution_ids":["https://openalex.org/I79891267"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yuan Fang","orcid":null},"institutions":[{"id":"https://openalex.org/I79891267","display_name":"Singapore Management University","ror":"https://ror.org/050qmg959","country_code":"SG","type":"education","lineage":["https://openalex.org/I79891267"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yuan Fang","raw_affiliation_strings":["Singapore Management University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Singapore Management University, Singapore","institution_ids":["https://openalex.org/I79891267"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chenghao Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chenghao Liu","raw_affiliation_strings":["Salesforce Research Asia, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Salesforce Research Asia, Singapore","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Steven C.H. Hoi","orcid":null},"institutions":[{"id":"https://openalex.org/I79891267","display_name":"Singapore Management University","ror":"https://ror.org/050qmg959","country_code":"SG","type":"education","lineage":["https://openalex.org/I79891267"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Steven C.H. Hoi","raw_affiliation_strings":["Salesforce Research Asia, Singapore","Singapore Management University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Salesforce Research Asia, Singapore","institution_ids":[]},{"raw_affiliation_string":"Singapore Management University, Singapore","institution_ids":["https://openalex.org/I79891267"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1520","last_page":"1526"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9865000247955322,"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/T10028","display_name":"Topic Modeling","score":0.9797000288963318,"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/locality","display_name":"Locality","score":0.715499997138977},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.6330000162124634},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.6323999762535095},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5968000292778015},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5392000079154968},{"id":"https://openalex.org/keywords/global-network","display_name":"Global network","score":0.4731999933719635},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46790000796318054}],"concepts":[{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.715499997138977},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.6330000162124634},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.6323999762535095},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6011000275611877},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5968000292778015},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5392000079154968},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.47620001435279846},{"id":"https://openalex.org/C123138037","wikidata":"https://www.wikidata.org/wiki/Q5570871","display_name":"Global network","level":2,"score":0.4731999933719635},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46790000796318054},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.45829999446868896},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4129999876022339},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36320000886917114},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3133000135421753},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.30809998512268066},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C2776230367","wikidata":"https://www.wikidata.org/wiki/Q7314222","display_name":"Representation theorem","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.2597000002861023}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.24963/ijcai.2021/210","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/210","pdf_url":"https://www.ijcai.org/proceedings/2021/0210.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2110.14322","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.14322","pdf_url":"https://arxiv.org/pdf/2110.14322","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2021/210","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/210","pdf_url":"https://www.ijcai.org/proceedings/2021/0210.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6960108870","display_name":null,"funder_award_id":"A20H6b0151","funder_id":"https://openalex.org/F4320320696","funder_display_name":"Agency for Science, Technology and Research"}],"funders":[{"id":"https://openalex.org/F4320320696","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3191845507.pdf","grobid_xml":"https://content.openalex.org/works/W3191845507.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Graph":[0],"neural":[1],"networks":[2],"(GNNs)":[3],"emerge":[4],"as":[5,133],"a":[6,21,55,63,88,130,134],"powerful":[7],"family":[8],"of":[9,39,65,91,101,136],"representation":[10],"learning":[11],"models":[12],"on":[13,107,111,149],"graphs.":[14],"To":[15,80],"derive":[16],"node":[17,56,82,126],"representations,":[18],"they":[19],"utilize":[20,81],"global":[22,73,97,114,138],"model":[23,75,132,139],"that":[24],"recursively":[25],"aggregates":[26],"information":[27,60],"from":[28,71],"the":[29,40,51,72,102,108,118,122,137,159],"neighboring":[30],"nodes.":[31,79],"However,":[32],"different":[33,37,43],"nodes":[34,106],"reside":[35],"at":[36],"parts":[38],"graph":[41,109],"in":[42],"local":[44,67,99,142],"contexts,":[45],"making":[46],"their":[47],"distributions":[48],"vary":[49],"across":[50,121],"graph.":[52,103],"Ideally,":[53],"how":[54],"receives":[57],"its":[58,66,141],"neighborhood":[59],"should":[61],"be":[62],"function":[64,135],"context,":[68],"to":[69,116],"diverge":[70],"GNN":[74,115],"shared":[76],"by":[77,93],"all":[78,105],"locality":[83],"without":[84],"overfitting,":[85],"we":[86,145],"propose":[87],"node-wise":[89],"localization":[90],"GNNs":[92],"accounting":[94],"for":[95],"both":[96],"and":[98,140,153],"aspects":[100],"Globally,":[104],"depend":[110],"an":[112],"underlying":[113],"encode":[117],"general":[119],"patterns":[120],"graph;":[123],"locally,":[124],"each":[125],"is":[127],"localized":[128],"into":[129],"unique":[131],"context.":[143],"Finally,":[144],"conduct":[146],"extensive":[147],"experiments":[148],"four":[150],"benchmark":[151],"graphs,":[152],"consistently":[154],"obtain":[155],"promising":[156],"performance":[157],"surpassing":[158],"state-of-the-art":[160],"GNNs.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2021-08-16T00:00:00"}
