{"id":"https://openalex.org/W2074258823","doi":"https://doi.org/10.1145/2492517.2492600","title":"Structure and attributes community detection benchmark and a novel selection method","display_name":"Structure and attributes community detection benchmark and a novel selection method","publication_year":2013,"publication_date":"2013-08-25","ids":{"openalex":"https://openalex.org/W2074258823","doi":"https://doi.org/10.1145/2492517.2492600","mag":"2074258823"},"language":"en","primary_location":{"id":"doi:10.1145/2492517.2492600","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2492517.2492600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining","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/A5001600741","display_name":"Haithum Elhadi","orcid":null},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haithum Elhadi","raw_affiliation_strings":["Illinois Institute of Technology, Chicago, IL","Comput. Sci. Dept., Illinois Inst. of Technol., Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology, Chicago, IL","institution_ids":["https://openalex.org/I180949307"]},{"raw_affiliation_string":"Comput. Sci. Dept., Illinois Inst. of Technol., Chicago, IL, USA","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023698748","display_name":"Gady Agam","orcid":null},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gady Agam","raw_affiliation_strings":["Illinois Institute of Technology, Chicago, IL","Comput. Sci. Dept., Illinois Inst. of Technol., Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology, Chicago, IL","institution_ids":["https://openalex.org/I180949307"]},{"raw_affiliation_string":"Comput. Sci. Dept., Illinois Inst. of Technol., Chicago, IL, USA","institution_ids":["https://openalex.org/I180949307"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I180949307"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20843447,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1474","last_page":"1476"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T10637","display_name":"Advanced Clustering Algorithms Research","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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9760000109672546,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.8252823352813721},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7846707105636597},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7225927710533142},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5868130922317505},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5348125100135803},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.48734912276268005},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4871211051940918},{"id":"https://openalex.org/keywords/community-structure","display_name":"Community structure","score":0.43162772059440613},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.424093097448349},{"id":"https://openalex.org/keywords/hierarchical-clustering-of-networks","display_name":"Hierarchical clustering of networks","score":0.41696032881736755},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.36379629373550415},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3628680109977722},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.23484301567077637},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19263190031051636}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8252823352813721},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7846707105636597},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7225927710533142},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5868130922317505},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5348125100135803},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.48734912276268005},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4871211051940918},{"id":"https://openalex.org/C133079900","wikidata":"https://www.wikidata.org/wiki/Q5155065","display_name":"Community structure","level":2,"score":0.43162772059440613},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.424093097448349},{"id":"https://openalex.org/C82261393","wikidata":"https://www.wikidata.org/wiki/Q17038699","display_name":"Hierarchical clustering of networks","level":5,"score":0.41696032881736755},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.36379629373550415},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3628680109977722},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.23484301567077637},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19263190031051636},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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:10.1145/2492517.2492600","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2492517.2492600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1602944680","https://openalex.org/W1964638370","https://openalex.org/W1971421925","https://openalex.org/W1975159990","https://openalex.org/W1977556410","https://openalex.org/W2015326995","https://openalex.org/W2023655578","https://openalex.org/W2024128809","https://openalex.org/W2036362885","https://openalex.org/W2040956707","https://openalex.org/W2079145444","https://openalex.org/W2111315907","https://openalex.org/W2131681506","https://openalex.org/W2145523428","https://openalex.org/W2165515835","https://openalex.org/W2290188864","https://openalex.org/W2377254088","https://openalex.org/W3099768174","https://openalex.org/W4244426546"],"related_works":["https://openalex.org/W2071479119","https://openalex.org/W2091202730","https://openalex.org/W2049068378","https://openalex.org/W2097005420","https://openalex.org/W2889551970","https://openalex.org/W2778018543","https://openalex.org/W2970886288","https://openalex.org/W3215188273","https://openalex.org/W3163986444","https://openalex.org/W2102717275"],"abstract_inverted_index":{"In":[0,28],"recent":[1],"years":[2],"due":[3],"to":[4,36,47,70],"the":[5,66,79,90,114],"rise":[6],"of":[7],"social,":[8],"biological,":[9],"and":[10,22,74,82,99,106,121],"other":[11],"rich":[12],"content":[13],"graphs,":[14],"several":[15],"new":[16,39,58,80],"graph":[17,67],"clustering":[18,59,76,95],"methods":[19],"using":[20],"structure":[21,51,68,73,98,103,120],"node's":[23],"attributes":[24,45],"have":[25],"been":[26],"introduced.":[27],"this":[29],"paper,":[30],"we":[31,88],"proposed":[32],"an":[33,44],"effective":[34],"benchmark":[35,42,81],"evaluate":[37],"these":[38],"methods.":[40,77,123],"Our":[41],"is":[43],"extension":[46],"a":[48,57],"widely":[49],"used":[50],"only":[52,104,109],"benchmark.":[53],"We":[54,111],"also":[55],"developed":[56],"method,":[60,63],"termed":[61],"Selection":[62,91,115],"that":[64,113,118],"uses":[65],"ambiguity":[69],"switch":[71],"between":[72],"attribute":[75,100,108,122],"Using":[78],"Normalized":[83],"Mutual":[84],"Information":[85],"(NMI)":[86],"metric,":[87],"evaluated":[89],"method":[92,105,116],"against":[93],"five":[94],"methods:":[96],"three":[97],"methods,":[101],"one":[102,107],"method.":[110],"showed":[112],"outperformed":[117],"state-of-art":[119]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}