{"id":"https://openalex.org/W4212955554","doi":"https://doi.org/10.1145/3487351.3488350","title":"Constant community identification in million scale networks using image thresholding algorithms","display_name":"Constant community identification in million scale networks using image thresholding algorithms","publication_year":2021,"publication_date":"2021-11-08","ids":{"openalex":"https://openalex.org/W4212955554","doi":"https://doi.org/10.1145/3487351.3488350"},"language":"en","primary_location":{"id":"doi:10.1145/3487351.3488350","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3487351.3488350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and 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/A5039850722","display_name":"Anjan Chowdhury","orcid":"https://orcid.org/0000-0003-1056-1568"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anjan Chowdhury","raw_affiliation_strings":["Indian Statistical Institute, Kolkata, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017449169","display_name":"Sriram Srinivasan","orcid":"https://orcid.org/0000-0003-0085-309X"},"institutions":[{"id":"https://openalex.org/I184840846","display_name":"Virginia Commonwealth University","ror":"https://ror.org/02nkdxk79","country_code":"US","type":"education","lineage":["https://openalex.org/I184840846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sriram Srinivasan","raw_affiliation_strings":["Virginia Commonwealth University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Commonwealth University","institution_ids":["https://openalex.org/I184840846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064623347","display_name":"Sanjukta Bhowmick","orcid":"https://orcid.org/0000-0001-8550-5371"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sanjukta Bhowmick","raw_affiliation_strings":["University of North Texas"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of North Texas","institution_ids":["https://openalex.org/I123534392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020991141","display_name":"Animesh Mukherjee","orcid":"https://orcid.org/0000-0003-4534-0044"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Animesh Mukherjee","raw_affiliation_strings":["IIT Kharagpur, Kharagpur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Kharagpur, Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079836374","display_name":"Kuntal Ghosh","orcid":"https://orcid.org/0000-0002-4431-1404"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kuntal Ghosh","raw_affiliation_strings":["Indian Statistical Institute, Kolkata, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1313,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49545106,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"116","last_page":"120"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9678999781608582,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9606000185012817,"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/thresholding","display_name":"Thresholding","score":0.8781047463417053},{"id":"https://openalex.org/keywords/constant","display_name":"Constant (computer programming)","score":0.7189870476722717},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6447802782058716},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5264801979064941},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5014724731445312},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4839392304420471},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.482696533203125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4802822768688202},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4600313901901245},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4560970067977905},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40557265281677246},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3690032958984375},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06625542044639587}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.8781047463417053},{"id":"https://openalex.org/C2777027219","wikidata":"https://www.wikidata.org/wiki/Q1284190","display_name":"Constant (computer programming)","level":2,"score":0.7189870476722717},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6447802782058716},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5264801979064941},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5014724731445312},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4839392304420471},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.482696533203125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4802822768688202},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4600313901901245},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4560970067977905},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40557265281677246},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3690032958984375},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06625542044639587},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3487351.3488350","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3487351.3488350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining","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":22,"referenced_works":["https://openalex.org/W2043147808","https://openalex.org/W2077110530","https://openalex.org/W2131681506","https://openalex.org/W2132202037","https://openalex.org/W2133059825","https://openalex.org/W2155167324","https://openalex.org/W2164998314","https://openalex.org/W2522886910","https://openalex.org/W2613193474","https://openalex.org/W2755088640","https://openalex.org/W2914663205","https://openalex.org/W2921266846","https://openalex.org/W2921480401","https://openalex.org/W2945531154","https://openalex.org/W2963322086","https://openalex.org/W2970350994","https://openalex.org/W3099768174","https://openalex.org/W3100808099","https://openalex.org/W6642118732","https://openalex.org/W6734320953","https://openalex.org/W6744788009","https://openalex.org/W6785465102"],"related_works":["https://openalex.org/W1542224353","https://openalex.org/W1661087619","https://openalex.org/W2116854923","https://openalex.org/W2750730210","https://openalex.org/W2236974868","https://openalex.org/W4312766348","https://openalex.org/W4233939244","https://openalex.org/W2952127465","https://openalex.org/W2028276520","https://openalex.org/W2164628286"],"abstract_inverted_index":{"Constant":[0],"communities,":[1,63],"i.e.,":[2],"groups":[3],"of":[4,12,25,38,72,104,114,117,119],"vertices":[5],"that":[6,127],"are":[7,18,89],"always":[8,90],"clustered":[9],"together,":[10],"independent":[11],"the":[13,22,61,66,76,115,134],"community":[14,26,39,93],"detection":[15,27,40,103],"algorithm":[16,97],"used,":[17],"necessary":[19],"for":[20,31,59],"reducing":[21],"inherent":[23],"stochasticity":[24],"results.":[28],"Current":[29],"methods":[30],"identifying":[32],"constant":[33,62,135],"communities":[34,105,136],"require":[35,100],"multiple":[36],"runs":[37],"algorithm(s).":[41],"This":[42],"process":[43],"is":[44,130],"extremely":[45],"time":[46],"consuming":[47],"and":[48,106,133,144],"not":[49,99],"scalable":[50],"to":[51,68,82,110],"large":[52,112],"networks.":[53],"We":[54,74],"propose":[55],"a":[56,69,92],"novel":[57],"approach":[58],"finding":[60],"by":[64],"transforming":[65],"problem":[67],"binary":[70],"classification":[71],"edges.":[73],"apply":[75],"Otsu":[77],"method":[78,129],"from":[79],"image":[80],"thresholding":[81],"classify":[83],"edges":[84],"based":[85],"on":[86,123],"whether":[87],"they":[88],"within":[91],"or":[94],"not.":[95],"Our":[96,121],"does":[98],"any":[101],"explicit":[102],"can":[107],"thus":[108],"scale":[109],"very":[111],"networks":[113],"order":[116],"millions":[118],"vertices.":[120],"results":[122],"real-world":[124],"graphs":[125],"show":[126],"our":[128],"significantly":[131],"faster":[132],"produced":[137],"have":[138],"higher":[139],"accuracy":[140],"(as":[141],"per":[142],"F1":[143],"NMI":[145],"scores)":[146],"than":[147],"state-of-the-art":[148],"baseline":[149],"methods.":[150]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
