{"id":"https://openalex.org/W4407953171","doi":"https://doi.org/10.1145/3701551.3703578","title":"Inductive Graph Few-shot Class Incremental Learning","display_name":"Inductive Graph Few-shot Class Incremental Learning","publication_year":2025,"publication_date":"2025-02-26","ids":{"openalex":"https://openalex.org/W4407953171","doi":"https://doi.org/10.1145/3701551.3703578"},"language":"en","primary_location":{"id":"doi:10.1145/3701551.3703578","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701551.3703578","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3701551.3703578","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102934651","display_name":"Yayong Li","orcid":"https://orcid.org/0000-0003-2534-1971"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yayong Li","raw_affiliation_strings":["The University of Queensland, Brisbane, Australia"],"raw_orcid":"https://orcid.org/0000-0003-2534-1971","affiliations":[{"raw_affiliation_string":"The University of Queensland, Brisbane, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008586469","display_name":"Peyman Moghadam","orcid":"https://orcid.org/0000-0002-8169-3560"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"government","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Peyman Moghadam","raw_affiliation_strings":["Commonwealth Scientific and Industrial Research Organisation, Brisbane, Australia"],"raw_orcid":"https://orcid.org/0000-0002-8169-3560","affiliations":[{"raw_affiliation_string":"Commonwealth Scientific and Industrial Research Organisation, Brisbane, Australia","institution_ids":["https://openalex.org/I1292875679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083735851","display_name":"Can Peng","orcid":"https://orcid.org/0000-0003-1673-2460"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Can Peng","raw_affiliation_strings":["University of Oxford, Oxford, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0003-1673-2460","affiliations":[{"raw_affiliation_string":"University of Oxford, Oxford, United Kingdom","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079833890","display_name":"Nan Ye","orcid":"https://orcid.org/0000-0001-5971-9202"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Nan Ye","raw_affiliation_strings":["The University of Queensland, Brisbane, Australia"],"raw_orcid":"https://orcid.org/0000-0001-5971-9202","affiliations":[{"raw_affiliation_string":"The University of Queensland, Brisbane, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002212263","display_name":"Piotr Koniusz","orcid":"https://orcid.org/0000-0002-6340-5289"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"government","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I4210101388","display_name":"Health Sciences and Nutrition","ror":"https://ror.org/0152bt112","country_code":"AU","type":"facility","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4210101388","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Piotr Koniusz","raw_affiliation_strings":["Commonwealth Scientific and Industrial Research Organisation, Canberra, Australia"],"raw_orcid":"https://orcid.org/0000-0002-6340-5289","affiliations":[{"raw_affiliation_string":"Commonwealth Scientific and Industrial Research Organisation, Canberra, Australia","institution_ids":["https://openalex.org/I4210101388","https://openalex.org/I1292875679"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"466","last_page":"474"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991000294685364,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991000294685364,"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/T12676","display_name":"Machine Learning and ELM","score":0.986299991607666,"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":0.9728999733924866,"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":0.6877256631851196},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.5708187818527222},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5168209671974182},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5115104913711548},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3967801332473755},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2774445116519928}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6877256631851196},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.5708187818527222},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5168209671974182},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5115104913711548},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3967801332473755},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2774445116519928},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3701551.3703578","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701551.3703578","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3701551.3703578","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701551.3703578","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1991418309","https://openalex.org/W2022322548","https://openalex.org/W2914304175","https://openalex.org/W2962898354","https://openalex.org/W3035342403","https://openalex.org/W3110791298","https://openalex.org/W3127228978","https://openalex.org/W3175270254","https://openalex.org/W3175771944","https://openalex.org/W3177494822","https://openalex.org/W3202568778","https://openalex.org/W3215627852","https://openalex.org/W4212857616","https://openalex.org/W4226091956","https://openalex.org/W4283645071","https://openalex.org/W4284672876","https://openalex.org/W4285216485","https://openalex.org/W4285605356","https://openalex.org/W4290877962","https://openalex.org/W4290927683","https://openalex.org/W4308624236","https://openalex.org/W4312572119","https://openalex.org/W4313005250","https://openalex.org/W4313143666","https://openalex.org/W4385613079","https://openalex.org/W4386071989","https://openalex.org/W4387097003","https://openalex.org/W4401856725","https://openalex.org/W6600120041"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2074502265","https://openalex.org/W4214877189","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2980279061","https://openalex.org/W2334685461","https://openalex.org/W2366718574"],"abstract_inverted_index":{"Node":[0],"classification":[1],"with":[2,55,83,147],"Graph":[3,17],"Neural":[4],"Networks":[5],"(GNN)":[6],"under":[7],"a":[8,26,118,135],"fixed":[9],"set":[10],"of":[11,74,144,149,167,181,194],"labels":[12],"is":[13],"well":[14],"studied,":[15],"while":[16,59],"Few-Shot":[18],"Class":[19],"Incremental":[20],"Learning":[21],"(GFSCIL),":[22],"which":[23,77],"involves":[24],"learning":[25],"GNN":[27],"classifier":[28],"as":[29,185],"graph":[30,82],"nodes":[31,58,148],"and":[32,125],"classes":[33,54,64,151,196,209],"growing":[34],"over":[35,199],"time":[36],"sporadically,":[37],"has":[38],"received":[39,152],"much":[40],"less":[41],"attention":[42],"despite":[43],"its":[44],"importance.":[45],"We":[46,215],"introduce":[47],"inductive":[48,92],"GFSCIL":[49],"that":[50],"continually":[51],"learns":[52],"novel":[53,119,150,168],"newly":[56],"emerging":[57],"maintaining":[60],"performance":[61],"on":[62,220],"old":[63,195,208],"without":[65],"accessing":[66],"previous":[67,100],"data.":[68,85],"This":[69],"addresses":[70],"the":[71,80,88,91,108,142,164,179,189,203,213,217],"practical":[72],"concern":[73],"transductive":[75,89],"GFSCIL,":[76,90],"requires":[78],"storing":[79],"entire":[81],"historical":[84],"Compared":[86],"to":[87,98,107,156,177,210],"setting":[93,143],"exacerbates":[94],"catastrophic":[95],"forgetting":[96],"due":[97],"inaccessible":[99],"data":[101],"during":[102],"incremental":[103,154,161],"training,":[104],"in":[105,153],"addition":[106],"overfitting":[109],"issue":[110],"caused":[111],"by":[112],"label":[113],"sparsity.":[114],"Thus,":[115],"we":[116,171,201],"propose":[117,172,202],"method,":[120,139],"called":[121],"Topology-based":[122],"class":[123,137,169,182],"Augmentation":[124],"Prototype":[126],"calibration":[127,176],"(TAP).":[128],"To":[129],"be":[130],"specific,":[131],"it":[132],"first":[133],"performs":[134],"topology-based":[136],"augmentation":[138],"helping":[140],"replicate":[141],"disjoint":[145],"subgraphs":[146],"sessions,":[155],"enhance":[157],"backbone":[158,186],"versatility.":[159],"In":[160],"learning,":[162],"given":[163],"limited":[165],"number":[166],"samples,":[170],"an":[173],"iterative":[174],"prototype":[175,204],"improve":[178],"separation":[180],"prototypes.":[183],"Furthermore,":[184],"fine-tuning":[187],"poses":[188],"feature":[190],"distribution":[191],"drift,":[192],"prototypes":[193],"start":[197],"failing":[198],"time,":[200],"shift":[205],"method":[206,219],"for":[207,212],"compensate":[211],"drift.":[214],"showcase":[216],"proposed":[218],"four":[221],"datasets.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
