{"id":"https://openalex.org/W3129083631","doi":"https://doi.org/10.1109/icoin50884.2021.9334012","title":"Network Completion: Beyond Matrix Completion","display_name":"Network Completion: Beyond Matrix Completion","publication_year":2021,"publication_date":"2021-01-13","ids":{"openalex":"https://openalex.org/W3129083631","doi":"https://doi.org/10.1109/icoin50884.2021.9334012","mag":"3129083631"},"language":"en","primary_location":{"id":"doi:10.1109/icoin50884.2021.9334012","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icoin50884.2021.9334012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Information Networking (ICOIN)","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/A5067894717","display_name":"Cong Tran","orcid":"https://orcid.org/0000-0001-9467-4978"},"institutions":[{"id":"https://openalex.org/I89015989","display_name":"Dankook University","ror":"https://ror.org/058pdbn81","country_code":"KR","type":"education","lineage":["https://openalex.org/I89015989"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Cong Tran","raw_affiliation_strings":["Dankook University, Yongin, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Dankook University, Yongin, Republic of Korea","institution_ids":["https://openalex.org/I89015989"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086873475","display_name":"Won-Yong Shin","orcid":"https://orcid.org/0000-0002-6533-3469"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Won-Yong Shin","raw_affiliation_strings":["School of Mathematics and Computing (Computational Science and Engineering), Yonsei University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Computing (Computational Science and Engineering), Yonsei University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5067894717"],"corresponding_institution_ids":["https://openalex.org/I89015989"],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50664668,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"11","issue":null,"first_page":"667","last_page":"670"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9940000176429749,"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":0.9940000176429749,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9878000020980835,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9840999841690063,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/matrix-completion","display_name":"Matrix completion","score":0.8425756692886353},{"id":"https://openalex.org/keywords/unobservable","display_name":"Unobservable","score":0.781842827796936},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7647099494934082},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.7369738817214966},{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.6631299257278442},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5343645811080933},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.478822261095047},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.47666338086128235},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4189165234565735},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.41405338048934937},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3560020327568054},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.31748971343040466},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13320773839950562},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.12755906581878662}],"concepts":[{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.8425756692886353},{"id":"https://openalex.org/C2780695315","wikidata":"https://www.wikidata.org/wiki/Q3799040","display_name":"Unobservable","level":2,"score":0.781842827796936},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7647099494934082},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.7369738817214966},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.6631299257278442},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5343645811080933},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.478822261095047},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.47666338086128235},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4189165234565735},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.41405338048934937},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3560020327568054},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31748971343040466},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13320773839950562},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.12755906581878662},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"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/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icoin50884.2021.9334012","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icoin50884.2021.9334012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Information Networking (ICOIN)","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":14,"referenced_works":["https://openalex.org/W1595449516","https://openalex.org/W2010541316","https://openalex.org/W2090463147","https://openalex.org/W2112681514","https://openalex.org/W2118034740","https://openalex.org/W2131492273","https://openalex.org/W2176446742","https://openalex.org/W2782034524","https://openalex.org/W2806115886","https://openalex.org/W3004555699","https://openalex.org/W3093178842","https://openalex.org/W6677111876","https://openalex.org/W6747748702","https://openalex.org/W6752306858"],"related_works":["https://openalex.org/W2614563012","https://openalex.org/W4293337373","https://openalex.org/W3144354057","https://openalex.org/W4301205717","https://openalex.org/W4288107728","https://openalex.org/W2788210652","https://openalex.org/W3093503721","https://openalex.org/W3213035342","https://openalex.org/W3152273675","https://openalex.org/W2972830027"],"abstract_inverted_index":{"Due":[0],"to":[1,21,39],"practical":[2],"reasons":[3],"such":[4],"as":[5],"limited":[6],"resources":[7],"and":[8,30,89,136,156],"privacy":[9],"settings":[10],"specified":[11],"by":[12],"users":[13],"on":[14,67],"social":[15],"media,":[16],"most":[17],"network":[18,49,68,117],"data":[19,50],"tend":[20],"be":[22,97],"only":[23],"partially":[24],"observed":[25],"with":[26],"both":[27],"missing":[28,31,42,105,128],"nodes":[29],"edges.":[32],"Thus,":[33],"it":[34],"is":[35,71,103],"of":[36,44,56,92,116,130,158],"paramount":[37],"importance":[38],"infer":[40],"the":[41,45,54,77,84,107,114,127,145,154,159],"parts":[43],"networks":[46],"since":[47],"incomplete":[48],"may":[51],"severely":[52],"degrade":[53],"performance":[55,142],"downstream":[57],"analyses.":[58],"In":[59],"this":[60],"paper,":[61],"we":[62,111,120,152],"provide":[63],"a":[64,72,87,90,101,141],"comprehensive":[65],"survey":[66],"completion,":[69],"which":[70],"more":[73],"challenging":[74],"task":[75],"than":[76],"well-studied":[78],"low-rank":[79],"matrix":[80,95],"completion":[81],"problem":[82,115],"in":[83],"sense":[85],"that":[86],"row":[88],"column":[91],"an":[93,131],"adjacency":[94],"shall":[96],"entirely":[98],"unobservable":[99],"when":[100],"node":[102],"completely":[104],"from":[106],"given":[108],"network.":[109],"Specifically,":[110],"first":[112],"define":[113],"completion.":[118],"Then,":[119],"review":[121],"two":[122,146,160],"state-of-the-art":[123],"algorithms":[124,147],"for":[125],"discovering":[126],"part":[129],"underlying":[132],"network,":[133],"namely":[134],"KronEM":[135],"DeepNC.":[137],"We":[138],"also":[139],"show":[140],"comparison":[143],"between":[144],"via":[148],"experimental":[149],"evaluation.":[150],"Finally,":[151],"discuss":[153],"potentials":[155],"limitations":[157],"algorithms.":[161]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}