{"id":"https://openalex.org/W2741514701","doi":"https://doi.org/10.24963/ijcai.2017/450","title":"When Does Label Propagation Fail? A View from a Network Generative Model","display_name":"When Does Label Propagation Fail? A View from a Network Generative Model","publication_year":2017,"publication_date":"2017-07-28","ids":{"openalex":"https://openalex.org/W2741514701","doi":"https://doi.org/10.24963/ijcai.2017/450","mag":"2741514701"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2017/450","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/450","pdf_url":"https://www.ijcai.org/proceedings/2017/0450.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2017/0450.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102513266","display_name":"Yuto Yamaguchi","orcid":null},"institutions":[{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuto Yamaguchi","raw_affiliation_strings":["AIST, Japan"],"affiliations":[{"raw_affiliation_string":"AIST, Japan","institution_ids":["https://openalex.org/I73613424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036534205","display_name":"Kohei Hayashi","orcid":"https://orcid.org/0000-0002-8758-8139"},"institutions":[{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Kohei Hayashi","raw_affiliation_strings":["AIST, Japan"],"affiliations":[{"raw_affiliation_string":"AIST, Japan","institution_ids":["https://openalex.org/I73613424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5036534205"],"corresponding_institution_ids":["https://openalex.org/I73613424"],"apc_list":null,"apc_paid":null,"fwci":1.3763,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.80603308,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3224","last_page":"3230"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994000196456909,"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/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9965999722480774,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9679999947547913,"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/node","display_name":"Node (physics)","score":0.730384349822998},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6502193808555603},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6338902115821838},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6074357628822327},{"id":"https://openalex.org/keywords/discretization","display_name":"Discretization","score":0.5368868112564087},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5288081169128418},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4845985174179077},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43677547574043274},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.41434890031814575},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3874117136001587},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.38603469729423523},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.295075386762619}],"concepts":[{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.730384349822998},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6502193808555603},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6338902115821838},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6074357628822327},{"id":"https://openalex.org/C73000952","wikidata":"https://www.wikidata.org/wiki/Q17007827","display_name":"Discretization","level":2,"score":0.5368868112564087},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5288081169128418},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4845985174179077},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43677547574043274},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.41434890031814575},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3874117136001587},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38603469729423523},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.295075386762619},{"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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:10.24963/ijcai.2017/450","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/450","pdf_url":"https://www.ijcai.org/proceedings/2017/0450.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2017/450","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/450","pdf_url":"https://www.ijcai.org/proceedings/2017/0450.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","score":0.6499999761581421,"display_name":"Gender equality"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335125","display_name":"RIKEN","ror":"https://ror.org/01sjwvz98"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2741514701.pdf","grobid_xml":"https://content.openalex.org/works/W2741514701.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1497443639","https://openalex.org/W1552297528","https://openalex.org/W1751403428","https://openalex.org/W1828512457","https://openalex.org/W1930572491","https://openalex.org/W1931149371","https://openalex.org/W1980347317","https://openalex.org/W1987810983","https://openalex.org/W2015326995","https://openalex.org/W2017199625","https://openalex.org/W2023655578","https://openalex.org/W2025266141","https://openalex.org/W2119998616","https://openalex.org/W2124672527","https://openalex.org/W2130707516","https://openalex.org/W2133095386","https://openalex.org/W2139823104","https://openalex.org/W2153959628","https://openalex.org/W2154455818","https://openalex.org/W2165636119","https://openalex.org/W2167768422","https://openalex.org/W2168346693","https://openalex.org/W2181900708","https://openalex.org/W2461425060","https://openalex.org/W2797925981","https://openalex.org/W2964029874","https://openalex.org/W4250803253","https://openalex.org/W4300579247","https://openalex.org/W6654002469","https://openalex.org/W6679690886","https://openalex.org/W6686091084","https://openalex.org/W6791858558"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4395044357","https://openalex.org/W4287117424","https://openalex.org/W4387506531","https://openalex.org/W2087346071","https://openalex.org/W2967848559","https://openalex.org/W4299831724"],"abstract_inverted_index":{"What":[0],"kinds":[1],"of":[2,16,84,96,107,118,157],"data":[3],"does":[4],"Label":[5],"Propagation":[6],"(LP)":[7],"work":[8,127],"best":[9,128],"on?":[10],"Can":[11],"we":[12,58,74,88,121],"justify":[13],"the":[14,60,76,81,94,101,115],"solution":[15,95],"LP":[17,22,65,85,124],"from":[18,66],"a":[19,24,38,67,104,155],"theoretical":[20,50,161],"standpoint?":[21],"is":[23,29,98],"semi-supervised":[25],"learning":[26],"algorithm":[27],"that":[28,90,108,123],"widely":[30],"used":[31],"to":[32,100],"predict":[33],"unobserved":[34],"node":[35,134,149],"labels":[36,150],"on":[37,43,129],"network":[39,77],"(e.g.,":[40],"user's":[41],"gender":[42],"an":[44],"SNS).":[45],"Despite":[46],"its":[47,49],"importance,":[48],"properties":[51],"remain":[52],"mostly":[53],"unexplored.":[54],"In":[55],"this":[56],"paper,":[57],"answer":[59],"above":[61],"questions":[62],"by":[63],"interpreting":[64],"statistical":[68],"viewpoint.":[69],"As":[70],"our":[71,160],"main":[72,112],"result,":[73],"identify":[75],"generative":[78,109],"model":[79],"behind":[80],"discretized":[82],"version":[83],"(DLP),":[86],"and":[87],"show":[89],"under":[91,154],"specific":[92],"conditions":[93],"DLP":[97],"equal":[99],"maximum":[102],"{\\it":[103],"posteriori}":[105],"estimate":[106],"model.":[110],"Our":[111,152],"result":[113],"reveals":[114],"critical":[116],"limitations":[117],"LP.":[119],"Specifically,":[120],"discover":[122],"would":[125],"not":[126],"networks":[130],"with":[131],"(1)":[132],"disassortative":[133],"labels,":[135],"(2)":[136],"clusters":[137],"having":[138],"different":[139],"edge":[140],"densities,":[141],"(3)":[142],"non-uniform":[143],"label":[144],"distributions,":[145],"or":[146],"(4)":[147],"unreliable":[148],"provided.":[151],"experiments":[153],"variety":[156],"settings":[158],"support":[159],"results.":[162]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
