{"id":"https://openalex.org/W2171935404","doi":"https://doi.org/10.1145/1772690.1772762","title":"Sampling community structure","display_name":"Sampling community structure","publication_year":2010,"publication_date":"2010-04-26","ids":{"openalex":"https://openalex.org/W2171935404","doi":"https://doi.org/10.1145/1772690.1772762","mag":"2171935404"},"language":"en","primary_location":{"id":"doi:10.1145/1772690.1772762","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1772690.1772762","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th international conference on World wide web","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/A5033767306","display_name":"Arun S. Maiya","orcid":null},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Arun S. Maiya","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060005215","display_name":"Tanya Berger\u2010Wolf","orcid":"https://orcid.org/0000-0001-7610-1412"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tanya Y. Berger-Wolf","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5033767306"],"corresponding_institution_ids":["https://openalex.org/I39422238"],"apc_list":null,"apc_paid":null,"fwci":11.5214,"has_fulltext":false,"cited_by_count":184,"citation_normalized_percentile":{"value":0.99039525,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"701","last_page":"710"},"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":0.9940000176429749,"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":0.9882000088691711,"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/sampling","display_name":"Sampling (signal processing)","score":0.7397438287734985},{"id":"https://openalex.org/keywords/community-structure","display_name":"Community structure","score":0.720279335975647},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7037457227706909},{"id":"https://openalex.org/keywords/stratified-sampling","display_name":"Stratified sampling","score":0.6392756700515747},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5728077292442322},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5435473918914795},{"id":"https://openalex.org/keywords/network-structure","display_name":"Network structure","score":0.4615139961242676},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41116929054260254},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3921792805194855},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2977060079574585},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22362151741981506}],"concepts":[{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.7397438287734985},{"id":"https://openalex.org/C133079900","wikidata":"https://www.wikidata.org/wiki/Q5155065","display_name":"Community structure","level":2,"score":0.720279335975647},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7037457227706909},{"id":"https://openalex.org/C49898467","wikidata":"https://www.wikidata.org/wiki/Q1517706","display_name":"Stratified sampling","level":2,"score":0.6392756700515747},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5728077292442322},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5435473918914795},{"id":"https://openalex.org/C2988224531","wikidata":"https://www.wikidata.org/wiki/Q20830730","display_name":"Network structure","level":2,"score":0.4615139961242676},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41116929054260254},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3921792805194855},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2977060079574585},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22362151741981506},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/1772690.1772762","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1772690.1772762","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th international conference on World wide web","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.332.2820","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.332.2820","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://compbio.cs.uic.edu/papers/Maiya_BergerWolf-SamplingCommunity-WWW10.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.352.3804","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.352.3804","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://arun.maiya.net/papers/maiya_etal-sampcomm.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320316838","display_name":"Kempe Foundation","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W635323286","https://openalex.org/W950821216","https://openalex.org/W1560267311","https://openalex.org/W1971421925","https://openalex.org/W1972978715","https://openalex.org/W1985625141","https://openalex.org/W1996134775","https://openalex.org/W1999653836","https://openalex.org/W2015953751","https://openalex.org/W2018047324","https://openalex.org/W2019968362","https://openalex.org/W2034331023","https://openalex.org/W2037859435","https://openalex.org/W2047940964","https://openalex.org/W2056760934","https://openalex.org/W2061099285","https://openalex.org/W2061901927","https://openalex.org/W2070099460","https://openalex.org/W2105848461","https://openalex.org/W2111708605","https://openalex.org/W2120043163","https://openalex.org/W2127048411","https://openalex.org/W2128891547","https://openalex.org/W2132013054","https://openalex.org/W2137253512","https://openalex.org/W2140610008","https://openalex.org/W2140975946","https://openalex.org/W2144885342","https://openalex.org/W2146008005","https://openalex.org/W2151078464","https://openalex.org/W2157747946","https://openalex.org/W2165363188","https://openalex.org/W3101413764","https://openalex.org/W3103786587","https://openalex.org/W3140968660","https://openalex.org/W4308830095","https://openalex.org/W6678043752"],"related_works":["https://openalex.org/W2387471420","https://openalex.org/W3042964584","https://openalex.org/W2356880469","https://openalex.org/W2383809451","https://openalex.org/W4206840145","https://openalex.org/W2370014976","https://openalex.org/W2350399852","https://openalex.org/W2378407977","https://openalex.org/W3047864323","https://openalex.org/W2075598034"],"abstract_inverted_index":{"We":[0,16,82],"propose":[1],"a":[2,76],"novel":[3],"method,":[4,21,63],"based":[5],"on":[6],"concepts":[7],"from":[8,50],"expander":[9],"graphs,":[10],"to":[11,101],"sample":[12],"communities":[13,54],"in":[14,31,44,55,107],"networks.":[15],"show":[17,65],"that":[18,45,66,93],"our":[19,62,85,94],"sampling":[20,95],"unlike":[22],"previous":[23],"techniques,":[24],"produces":[25],"subgraphs":[26,37],"representative":[27],"of":[28,48,69,78],"community":[29,70,105],"structure":[30],"the":[32,56,67,108],"original":[33],"network.":[34,57,110],"These":[35],"generated":[36],"may":[38,72],"be":[39,73,99],"viewed":[40],"as":[41],"stratified":[42],"samples":[43,59],"they":[46],"consist":[47],"members":[49],"most":[51],"or":[52],"all":[53],"Using":[58],"produced":[60],"by":[61],"we":[64],"problem":[68],"detection":[71],"recast":[74],"into":[75],"case":[77],"statistical":[79],"relational":[80],"learning.":[81],"empirically":[83],"evaluate":[84],"approach":[86],"against":[87],"several":[88],"real-world":[89],"datasets":[90],"and":[91,103],"demonstrate":[92],"method":[96],"can":[97],"effectively":[98],"used":[100],"infer":[102],"approximate":[104],"affiliation":[106],"larger":[109]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":12},{"year":2017,"cited_by_count":12},{"year":2016,"cited_by_count":13},{"year":2015,"cited_by_count":16},{"year":2014,"cited_by_count":16},{"year":2013,"cited_by_count":17},{"year":2012,"cited_by_count":17}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}