{"id":"https://openalex.org/W4249108811","doi":"https://doi.org/10.1109/asonam.2016.7752214","title":"Network completion via joint node clustering and similarity learning","display_name":"Network completion via joint node clustering and similarity learning","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W4249108811","doi":"https://doi.org/10.1109/asonam.2016.7752214"},"language":"en","primary_location":{"id":"doi:10.1109/asonam.2016.7752214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam.2016.7752214","pdf_url":null,"source":{"id":"https://openalex.org/S4363608003","display_name":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","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/A5034151597","display_name":"Dimitrios Rafailidis","orcid":"https://orcid.org/0000-0002-7366-3716"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Dimitrios Rafailidis","raw_affiliation_strings":["Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012367814","display_name":"F\u00e1bio Crestani","orcid":"https://orcid.org/0000-0001-8672-0700"},"institutions":[{"id":"https://openalex.org/I57201433","display_name":"Universit\u00e0 della Svizzera italiana","ror":"https://ror.org/03c4atk17","country_code":"CH","type":"education","lineage":["https://openalex.org/I57201433"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Fabio Crestani","raw_affiliation_strings":["Faculty of Informatics, Universit\u00e0 della Svizzera italiana (USI), Lugano, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Informatics, Universit\u00e0 della Svizzera italiana (USI), Lugano, Switzerland","institution_ids":["https://openalex.org/I57201433"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.29023758,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"63","last_page":"68"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9884999990463257,"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":0.9864000082015991,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.729620635509491},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7186785936355591},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6746741533279419},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5589738488197327},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5424672961235046},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5402336716651917},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3933679461479187},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1025453507900238}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.729620635509491},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7186785936355591},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6746741533279419},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5589738488197327},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5424672961235046},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5402336716651917},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3933679461479187},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1025453507900238},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","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},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asonam.2016.7752214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam.2016.7752214","pdf_url":null,"source":{"id":"https://openalex.org/S4363608003","display_name":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","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":28,"referenced_works":["https://openalex.org/W1595449516","https://openalex.org/W1864134408","https://openalex.org/W1967863365","https://openalex.org/W1993591232","https://openalex.org/W2012921801","https://openalex.org/W2052575990","https://openalex.org/W2097820631","https://openalex.org/W2105250718","https://openalex.org/W2111315907","https://openalex.org/W2112429379","https://openalex.org/W2117420919","https://openalex.org/W2131492273","https://openalex.org/W2135029798","https://openalex.org/W2142562746","https://openalex.org/W2154415691","https://openalex.org/W2155461593","https://openalex.org/W2165515835","https://openalex.org/W2199277097","https://openalex.org/W2219154195","https://openalex.org/W2263288921","https://openalex.org/W2340622084","https://openalex.org/W2405459681","https://openalex.org/W3102647957","https://openalex.org/W3122868618","https://openalex.org/W6674539747","https://openalex.org/W6680012447","https://openalex.org/W6681259990","https://openalex.org/W6682991666"],"related_works":["https://openalex.org/W2804364458","https://openalex.org/W4298130764","https://openalex.org/W2132641928","https://openalex.org/W4310225030","https://openalex.org/W2090259340","https://openalex.org/W1996130883","https://openalex.org/W2748574964","https://openalex.org/W2393816671","https://openalex.org/W2158836806","https://openalex.org/W2098964748"],"abstract_inverted_index":{"In":[0,155],"this":[1],"study,":[2],"we":[3,30,97,157],"investigate":[4],"the":[5,12,15,33,37,45,51,67,94,102,107,110,113,116,130,134,138,142,147,150,164,185],"problem":[6,167],"of":[7,21,40,133,141],"network":[8,34,72,165],"completion":[9,73,166,190],"by":[10,35],"considering":[11],"similarities":[13,92,140],"between":[14],"node":[16,52,103,143],"attributes.":[17],"Given":[18],"a":[19,71,123],"sample":[20],"observed":[22,135],"nodes":[23],"with":[24,137],"their":[25],"incident":[26],"edges,":[27,47],"how":[28],"can":[29],"efficiently":[31],"reconstruct":[32],"completing":[36,66],"missing":[38,46],"edges":[39,136],"unobserved":[41],"nodes?":[42],"Apart":[43],"from":[44,86,179],"in":[48,112],"real":[49,175],"settings":[50],"attributes":[53,117],"may":[54,62,118],"be":[55,119],"partially":[56],"missing,":[57],"as":[58,60],"well":[59],"they":[61],"introduce":[63],"noise":[64,108],"when":[65],"network.":[68],"We":[69,121],"propose":[70,158],"method":[74],"based":[75,100],"on":[76,101,173],"joint":[77,124],"clustering":[78],"and":[79,109,181],"similarity":[80],"learning.":[81],"The":[82],"proposed":[83,186],"approach":[84,187],"differs":[85],"competitive":[87],"strategies,":[88],"which":[89],"consider":[90],"attribute-based":[91],"at":[93,146],"node-level.":[95],"First":[96],"generate":[98],"clusters":[99,151],"attributes,":[104,144],"thus":[105],"reducing":[106],"sparsity":[111],"case":[114],"that":[115,184],"missing.":[120],"design":[122],"objective":[125],"function":[126],"to":[127,162,193],"jointly":[128],"factorize":[129],"adjacency":[131],"matrix":[132],"cluster-based":[139],"while":[145],"same":[148],"time":[149],"are":[152],"adapted,":[153],"accordingly.":[154],"addition,":[156],"an":[159],"optimization":[160],"algorithm":[161],"solve":[163],"via":[168],"alternating":[169],"minimization.":[170],"Our":[171],"experiments":[172],"two":[174],"world":[176],"social":[177],"networks":[178],"Facebook":[180],"Google+":[182],"show":[183],"achieves":[188],"high":[189],"accuracy,":[191],"compared":[192],"other":[194],"state-of-the-art":[195],"methods.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
