{"id":"https://openalex.org/W2012720017","doi":"https://doi.org/10.1145/2020408.2020513","title":"Triangle listing in massive networks and its applications","display_name":"Triangle listing in massive networks and its applications","publication_year":2011,"publication_date":"2011-08-21","ids":{"openalex":"https://openalex.org/W2012720017","doi":"https://doi.org/10.1145/2020408.2020513","mag":"2012720017"},"language":"en","primary_location":{"id":"doi:10.1145/2020408.2020513","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2020408.2020513","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5102141433","display_name":"Shumo Chu","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Shumo Chu","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore","Nanyang Technological University, Singapore, SINGAPORE#TAB#"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Nanyang Technological University, Singapore, SINGAPORE#TAB#","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016082884","display_name":"James Cheng","orcid":"https://orcid.org/0000-0001-6313-6288"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"James Cheng","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore","Nanyang Technological University, Singapore, SINGAPORE#TAB#"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Nanyang Technological University, Singapore, SINGAPORE#TAB#","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102141433"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":8.5456,"has_fulltext":false,"cited_by_count":144,"citation_normalized_percentile":{"value":0.98310206,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"672","last_page":"680"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9987000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.758766770362854},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6761132478713989},{"id":"https://openalex.org/keywords/listing","display_name":"Listing (finance)","score":0.6049603819847107},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5754964351654053},{"id":"https://openalex.org/keywords/clustering-coefficient","display_name":"Clustering coefficient","score":0.5179244875907898},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5099972486495972},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4453841745853424},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4382709562778473},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.42905905842781067},{"id":"https://openalex.org/keywords/algorithm-design","display_name":"Algorithm design","score":0.4154152274131775},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1280021369457245},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.0908094048500061}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.758766770362854},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6761132478713989},{"id":"https://openalex.org/C2779820595","wikidata":"https://www.wikidata.org/wiki/Q798505","display_name":"Listing (finance)","level":2,"score":0.6049603819847107},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5754964351654053},{"id":"https://openalex.org/C22047676","wikidata":"https://www.wikidata.org/wiki/Q898680","display_name":"Clustering coefficient","level":3,"score":0.5179244875907898},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5099972486495972},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4453841745853424},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4382709562778473},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.42905905842781067},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.4154152274131775},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1280021369457245},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0908094048500061},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","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:10.1145/2020408.2020513","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2020408.2020513","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320751","display_name":"Ministry of Education - Singapore","ror":"https://ror.org/01kcva023"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W950821216","https://openalex.org/W1489509891","https://openalex.org/W1620903941","https://openalex.org/W1967066104","https://openalex.org/W1988671533","https://openalex.org/W1991858502","https://openalex.org/W1993355353","https://openalex.org/W1998341696","https://openalex.org/W2000979164","https://openalex.org/W2005887911","https://openalex.org/W2006714486","https://openalex.org/W2013414394","https://openalex.org/W2015960500","https://openalex.org/W2016311778","https://openalex.org/W2018978908","https://openalex.org/W2038142281","https://openalex.org/W2061901927","https://openalex.org/W2063597636","https://openalex.org/W2070593017","https://openalex.org/W2080745194","https://openalex.org/W2095117703","https://openalex.org/W2101267973","https://openalex.org/W2102322109","https://openalex.org/W2109469951","https://openalex.org/W2110814195","https://openalex.org/W2111787123","https://openalex.org/W2112090702","https://openalex.org/W2113513143","https://openalex.org/W2117071406","https://openalex.org/W2125725243","https://openalex.org/W2131183411","https://openalex.org/W2137572956","https://openalex.org/W2142599626","https://openalex.org/W2153624566","https://openalex.org/W2154191591","https://openalex.org/W2157948169","https://openalex.org/W2158432527","https://openalex.org/W2161455936","https://openalex.org/W2588458088","https://openalex.org/W4255281402"],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2935909890","https://openalex.org/W2778153218","https://openalex.org/W2758277628","https://openalex.org/W1531601525","https://openalex.org/W2132996594"],"abstract_inverted_index":{"Triangle":[0],"listing":[1,36,64],"is":[2,99,112],"one":[3],"of":[4,18,25,49],"the":[5,16,23,46,55,116],"fundamental":[6],"algorithmic":[7],"problems":[8],"whose":[9,41],"solution":[10],"has":[11],"numerous":[12],"applications":[13],"especially":[14],"in":[15],"analysis":[17],"complex":[19],"networks,":[20],"such":[21],"as":[22],"computation":[24],"clustering":[26],"coefficient,":[27],"transitivity,":[28],"triangular":[29],"connectivity,":[30],"etc.":[31],"Existing":[32],"algorithms":[33,80],"for":[34,94],"triangle":[35,63,95,119],"are":[37,86],"mainly":[38],"in-memory":[39],"algorithms,":[40],"performance":[42],"cannot":[43,58],"scale":[44],"with":[45],"massive":[47],"volume":[48],"today's":[50],"fast":[51],"growing":[52],"networks.":[53],"When":[54],"input":[56],"graph":[57],"fit":[59],"into":[60],"main":[61],"memory,":[62],"requires":[65],"random":[66,103],"disk":[67,104],"accesses":[68],"that":[69,109],"can":[70],"incur":[71],"prohibitively":[72],"large":[73],"I/O":[74],"cost.":[75],"Some":[76],"streaming":[77],"and":[78,101,114],"sampling":[79],"have":[81],"been":[82],"proposed":[83],"but":[84],"these":[85],"approximation":[87],"algorithms.":[88],"We":[89],"propose":[90],"an":[91],"I/O-efficient":[92],"algorithm":[93,98,111],"listing.":[96],"Our":[97,106],"exact":[100],"avoids":[102],"access.":[105],"results":[107],"show":[108],"our":[110],"scalable":[113],"outperforms":[115],"state-of-the-art":[117],"local":[118],"estimation":[120],"algorithm.":[121]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":14},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":12},{"year":2017,"cited_by_count":16},{"year":2016,"cited_by_count":15},{"year":2015,"cited_by_count":17},{"year":2014,"cited_by_count":17},{"year":2013,"cited_by_count":10},{"year":2012,"cited_by_count":8}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}