{"id":"https://openalex.org/W2773356553","doi":"https://doi.org/10.1145/3155133.3155170","title":"Graph-based Clustering with Background Knowledge","display_name":"Graph-based Clustering with Background Knowledge","publication_year":2017,"publication_date":"2017-12-07","ids":{"openalex":"https://openalex.org/W2773356553","doi":"https://doi.org/10.1145/3155133.3155170","mag":"2773356553"},"language":"en","primary_location":{"id":"doi:10.1145/3155133.3155170","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3155133.3155170","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighth International Symposium on Information and Communication Technology","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/A5079778040","display_name":"Viet-Vu Vu","orcid":"https://orcid.org/0000-0001-5579-8783"},"institutions":[{"id":"https://openalex.org/I177233841","display_name":"Vietnam National University, Hanoi","ror":"https://ror.org/02jmfj006","country_code":"VN","type":"education","lineage":["https://openalex.org/I177233841"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Viet-Vu Vu","raw_affiliation_strings":["The Information Technology Institute, Vietnam National University, Hanoi, Hanoi, Vietnam"],"affiliations":[{"raw_affiliation_string":"The Information Technology Institute, Vietnam National University, Hanoi, Hanoi, Vietnam","institution_ids":["https://openalex.org/I177233841"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052419914","display_name":"Hong-Quan Do","orcid":"https://orcid.org/0000-0003-0325-4797"},"institutions":[{"id":"https://openalex.org/I177233841","display_name":"Vietnam National University, Hanoi","ror":"https://ror.org/02jmfj006","country_code":"VN","type":"education","lineage":["https://openalex.org/I177233841"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Hong-Quan Do","raw_affiliation_strings":["The Information Technology Institute, Vietnam National University, Hanoi, Hanoi, Vietnam"],"affiliations":[{"raw_affiliation_string":"The Information Technology Institute, Vietnam National University, Hanoi, Hanoi, Vietnam","institution_ids":["https://openalex.org/I177233841"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5079778040"],"corresponding_institution_ids":["https://openalex.org/I177233841"],"apc_list":null,"apc_paid":null,"fwci":0.5851,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.76736422,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"167","last_page":"172"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9987999796867371,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9987999796867371,"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":0.9969000220298767,"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/T11106","display_name":"Data Management and Algorithms","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/cluster-analysis","display_name":"Cluster analysis","score":0.9149568676948547},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.723515510559082},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6777648329734802},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.6767216920852661},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.6718674302101135},{"id":"https://openalex.org/keywords/constrained-clustering","display_name":"Constrained clustering","score":0.6305826902389526},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.6300029158592224},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.5856943726539612},{"id":"https://openalex.org/keywords/single-linkage-clustering","display_name":"Single-linkage clustering","score":0.5143085718154907},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5037650465965271},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46852701902389526},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.44989296793937683},{"id":"https://openalex.org/keywords/conceptual-clustering","display_name":"Conceptual clustering","score":0.43042439222335815},{"id":"https://openalex.org/keywords/brown-clustering","display_name":"Brown clustering","score":0.42688918113708496},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4235316216945648},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37774866819381714},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36212223768234253},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.16229066252708435}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.9149568676948547},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.723515510559082},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6777648329734802},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.6767216920852661},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.6718674302101135},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.6305826902389526},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.6300029158592224},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.5856943726539612},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.5143085718154907},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5037650465965271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46852701902389526},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.44989296793937683},{"id":"https://openalex.org/C39235581","wikidata":"https://www.wikidata.org/wiki/Q5158434","display_name":"Conceptual clustering","level":5,"score":0.43042439222335815},{"id":"https://openalex.org/C167984511","wikidata":"https://www.wikidata.org/wiki/Q17003931","display_name":"Brown clustering","level":5,"score":0.42688918113708496},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4235316216945648},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37774866819381714},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36212223768234253},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.16229066252708435}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3155133.3155170","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3155133.3155170","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighth International Symposium on Information and Communication Technology","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":21,"referenced_works":["https://openalex.org/W9886305","https://openalex.org/W80917968","https://openalex.org/W143174683","https://openalex.org/W1516407653","https://openalex.org/W1556320907","https://openalex.org/W1983619063","https://openalex.org/W1987865517","https://openalex.org/W1995692149","https://openalex.org/W2033403400","https://openalex.org/W2052478943","https://openalex.org/W2078979416","https://openalex.org/W2089923519","https://openalex.org/W2096100960","https://openalex.org/W2102524069","https://openalex.org/W2130453506","https://openalex.org/W2153233077","https://openalex.org/W2170896428","https://openalex.org/W2610360795","https://openalex.org/W2730841449","https://openalex.org/W3105265400","https://openalex.org/W3120740533"],"related_works":["https://openalex.org/W2087424554","https://openalex.org/W2622412490","https://openalex.org/W2187059365","https://openalex.org/W1997571094","https://openalex.org/W2160785859","https://openalex.org/W2315511185","https://openalex.org/W1569024462","https://openalex.org/W3140018618","https://openalex.org/W4238952262","https://openalex.org/W2556924671"],"abstract_inverted_index":{"Since":[0],"2000,":[1],"when":[2],"clustering":[3,16,32,43,48,91,101,124],"with":[4,127],"side":[5,25,54],"information":[6,26,55],"is":[7,106],"introduced":[8],"in":[9,30,74,82,99],"the":[10,31,66,75,87,100],"first":[11],"time,":[12],"so":[13],"many":[14],"semi-supervised":[15,47,88],"algorithms":[17],"have":[18],"been":[19,35],"presented.":[20],"Semi-supervised":[21],"clustering,":[22],"that":[23,118],"integrates":[24],"(seeds":[27],"or":[28],"constraints)":[29],"process,":[33],"has":[34],"known":[36],"as":[37],"a":[38],"good":[39,123],"strategy":[40],"to":[41,65],"boost":[42],"results.":[44],"In":[45],"general,":[46],"focuses":[49],"on":[50,111],"two":[51],"kind":[52],"of":[53,68],"including":[56],"seeds":[57,71,98],"and":[58,72,97],"constraints,":[59],"not":[60],"much":[61],"attention":[62],"was":[63],"given":[64],"topic":[67],"using":[69],"both":[70,95],"constraints":[73,96],"same":[76],"algorithm.":[77],"To":[78],"address":[79],"this":[80,83],"problem,":[81],"paper,":[84],"we":[85],"extend":[86],"graph":[89],"based":[90],"(SSGC)":[92],"by":[93],"embedding":[94],"process;":[102],"our":[103,119],"new":[104],"algorithm":[105],"called":[107],"MCSSGC.":[108],"Experiments":[109],"conducted":[110],"real":[112],"data":[113],"sets":[114],"from":[115],"UCI":[116],"show":[117],"method":[120],"can":[121],"produce":[122],"results":[125],"compared":[126],"SSGC.":[128]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}