{"id":"https://openalex.org/W3210535434","doi":"https://doi.org/10.1145/3459637.3482469","title":"Rectifying Pseudo Labels","display_name":"Rectifying Pseudo Labels","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3210535434","doi":"https://doi.org/10.1145/3459637.3482469","mag":"3210535434"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482469","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482469","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","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/A5038606050","display_name":"Zhihui Hu","orcid":"https://orcid.org/0000-0002-3002-8691"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhihui Hu","raw_affiliation_strings":["Defense Innovation Institute, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Defense Innovation Institute, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017668787","display_name":"Guang Kou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guang Kou","raw_affiliation_strings":["Defense Innovation Institute, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Defense Innovation Institute, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100425887","display_name":"Haoyu Zhang","orcid":"https://orcid.org/0000-0002-3896-170X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haoyu Zhang","raw_affiliation_strings":["Defense Innovation Institute, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Defense Innovation Institute, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100368048","display_name":"Na Li","orcid":"https://orcid.org/0000-0001-9545-3050"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Na Li","raw_affiliation_strings":["Defense Innovation Institute, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Defense Innovation Institute, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037028903","display_name":"Ke Yang","orcid":"https://orcid.org/0000-0001-6617-9558"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ke Yang","raw_affiliation_strings":["Defense Innovation Institute, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Defense Innovation Institute, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100383303","display_name":"Lin Liu","orcid":"https://orcid.org/0000-0002-5930-8881"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Liu","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"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":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"720","last_page":"729"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9937000274658203,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9855999946594238,"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":0.7550731897354126},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6900389194488525},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6686410903930664},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5728853940963745},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.563611626625061},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.5396715402603149},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5326784253120422},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5244420170783997},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5198643207550049},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4685916304588318},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4626290500164032},{"id":"https://openalex.org/keywords/euclidean-geometry","display_name":"Euclidean geometry","score":0.42322707176208496},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41268664598464966},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40970736742019653},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35159146785736084},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.18352457880973816},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10587948560714722}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7550731897354126},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6900389194488525},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6686410903930664},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5728853940963745},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.563611626625061},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.5396715402603149},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5326784253120422},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5244420170783997},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5198643207550049},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4685916304588318},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4626290500164032},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.42322707176208496},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41268664598464966},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40970736742019653},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35159146785736084},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.18352457880973816},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10587948560714722},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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:10.1145/3459637.3482469","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482469","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2011430131","https://openalex.org/W2022322548","https://openalex.org/W2142838865","https://openalex.org/W2154851992","https://openalex.org/W2165874743","https://openalex.org/W2171180835","https://openalex.org/W2194775991","https://openalex.org/W2423557781","https://openalex.org/W2468907370","https://openalex.org/W2608787653","https://openalex.org/W2618530766","https://openalex.org/W2624431344","https://openalex.org/W2784814091","https://openalex.org/W2788512147","https://openalex.org/W2807021761","https://openalex.org/W2883725317","https://openalex.org/W2924719072","https://openalex.org/W2963169753","https://openalex.org/W2963782635","https://openalex.org/W2963858333","https://openalex.org/W2964311892","https://openalex.org/W2965556524","https://openalex.org/W2996028985","https://openalex.org/W2997212544","https://openalex.org/W2998269939","https://openalex.org/W3012816161","https://openalex.org/W3035287707","https://openalex.org/W3035684973","https://openalex.org/W3039075121","https://openalex.org/W3099023595","https://openalex.org/W3100848837","https://openalex.org/W3100993589","https://openalex.org/W3104097132","https://openalex.org/W3108655343","https://openalex.org/W3190214286"],"related_works":["https://openalex.org/W2090152127","https://openalex.org/W1965169884","https://openalex.org/W3125580510","https://openalex.org/W2008939113","https://openalex.org/W2033213447","https://openalex.org/W14679004","https://openalex.org/W1566651525","https://openalex.org/W2977652649","https://openalex.org/W2318206461","https://openalex.org/W37157938"],"abstract_inverted_index":{"Graph":[0,52],"Convolutional":[1,53],"Networks":[2,54],"(GCNs)":[3],"are":[4],"powerful":[5],"representation":[6],"learning":[7],"methods":[8,136],"for":[9,91],"non-Euclidean":[10,19],"data.":[11,39],"Compared":[12],"with":[13,61],"the":[14,18,37,58,78,96,101,105,123,138],"Euclidean":[15],"data,":[16],"labeling":[17],"data":[20,32],"is":[21],"more":[22],"expensive.":[23],"Meanwhile,":[24],"most":[25,35],"existing":[26],"GCNs":[27],"only":[28],"utilize":[29],"few":[30],"labeled":[31],"but":[33],"ignore":[34],"of":[36],"unlabeled":[38],"To":[40],"address":[41],"this":[42],"issue,":[43],"we":[44,86],"design":[45,87],"a":[46],"novel":[47],"end-to-end":[48],"Iterative":[49,63],"Feature":[50,64],"Clustering":[51,65],"(IFC-GCN)":[55],"that":[56,115,132],"enhances":[57],"standard":[59],"GCN":[60],"an":[62,88],"(IFC)":[66],"module.":[67],"The":[68],"proposed":[69,117],"IFC":[70,118],"module":[71,119],"constrains":[72],"node":[73,106,124,140],"features":[74,107],"iteratively":[75],"based":[76],"on":[77,128,137],"predicted":[79],"pseudo":[80,102],"labels":[81,103],"and":[82,104,111],"feature":[83],"clustering.":[84],"Further,":[85],"EM-like":[89],"framework":[90],"IFC-GCN":[92,133],"training,":[93],"which":[94],"improves":[95],"network":[97],"performance":[98],"by":[99],"rectifying":[100],"alternately.":[108],"Theoretical":[109],"analysis":[110],"experimental":[112],"results":[113,127],"show":[114],"our":[116],"can":[120],"effectively":[121],"modify":[122],"features.":[125],"Experimental":[126],"public":[129],"datasets":[130],"demonstrate":[131],"outperforms":[134],"state-of-the-art":[135],"semi-supervised":[139],"classification":[141],"task.":[142]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}