{"id":"https://openalex.org/W2902307923","doi":"https://doi.org/10.1109/icpr.2018.8546193","title":"Scalable spectral clustering with cosine similarity","display_name":"Scalable spectral clustering with cosine similarity","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2902307923","doi":"https://doi.org/10.1109/icpr.2018.8546193","mag":"2902307923"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8546193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8546193","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","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/A5101466169","display_name":"Guangliang Chen","orcid":"https://orcid.org/0000-0001-8334-3727"},"institutions":[{"id":"https://openalex.org/I51504820","display_name":"San Jose State University","ror":"https://ror.org/04qyvz380","country_code":"US","type":"education","lineage":["https://openalex.org/I51504820"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Guangliang Chen","raw_affiliation_strings":["Department of Mathematics and Statistics, San J\u00f3se State University, San J\u00f3se, California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, San J\u00f3se State University, San J\u00f3se, California","institution_ids":["https://openalex.org/I51504820"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101466169"],"corresponding_institution_ids":["https://openalex.org/I51504820"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"314","last_page":"319"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9983999729156494,"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":0.9983999729156494,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9972000122070312,"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/cosine-similarity","display_name":"Cosine similarity","score":0.8041272759437561},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.7561091184616089},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7431561946868896},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6471893787384033},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.5868697166442871},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5750318169593811},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.5146011114120483},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5123118162155151},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5079341530799866},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.502129316329956},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5001180171966553},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.49939966201782227},{"id":"https://openalex.org/keywords/matrix-multiplication","display_name":"Matrix multiplication","score":0.4692870080471039},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4143815040588379},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4110109210014343},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34611254930496216},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2605419158935547},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22466403245925903},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.1186712384223938},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.08923253417015076}],"concepts":[{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.8041272759437561},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.7561091184616089},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7431561946868896},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6471893787384033},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.5868697166442871},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5750318169593811},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.5146011114120483},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5123118162155151},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5079341530799866},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.502129316329956},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5001180171966553},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.49939966201782227},{"id":"https://openalex.org/C17349429","wikidata":"https://www.wikidata.org/wiki/Q1049914","display_name":"Matrix multiplication","level":3,"score":0.4692870080471039},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4143815040588379},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4110109210014343},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34611254930496216},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2605419158935547},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22466403245925903},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.1186712384223938},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.08923253417015076},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8546193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8546193","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W40976687","https://openalex.org/W137313310","https://openalex.org/W200434350","https://openalex.org/W1969903078","https://openalex.org/W1986007546","https://openalex.org/W2009581456","https://openalex.org/W2089609272","https://openalex.org/W2116810533","https://openalex.org/W2121947440","https://openalex.org/W2132914434","https://openalex.org/W2134370969","https://openalex.org/W2165874743","https://openalex.org/W2610068334","https://openalex.org/W2806247367","https://openalex.org/W2964012263","https://openalex.org/W4213367101","https://openalex.org/W6608197349","https://openalex.org/W6684578312","https://openalex.org/W6737187793"],"related_works":["https://openalex.org/W2885181216","https://openalex.org/W2902307923","https://openalex.org/W2293771254","https://openalex.org/W3209524672","https://openalex.org/W3121828480","https://openalex.org/W2039875226","https://openalex.org/W4221142455","https://openalex.org/W2914631005","https://openalex.org/W2123154672","https://openalex.org/W2032786851"],"abstract_inverted_index":{"We":[0,38,69,118],"propose":[1],"a":[2,49,56],"unified":[3],"scalable":[4,129],"computing":[5],"framework":[6],"for":[7,61],"three":[8],"versions":[9],"of":[10,35,54],"spectral":[11,75],"clustering":[12,76],"-":[13],"Normalized":[14],"Cut":[15],"(Shi":[16],"and":[17,25,29,95,114],"Malik,":[18],"2000),":[19],"the":[20,33,41,86,101,132],"Ng-Jordan-Weiss":[21],"(NJW)":[22],"algorithm":[23,105,130],"(2001),":[24],"Diffusion":[26],"Maps":[27],"(Coifman":[28],"Lafon,":[30],"2006),":[31],"in":[32,72],"setting":[34],"cosine":[36],"similarity.":[37],"assume":[39],"that":[40,71],"input":[42],"data":[43,65,87,138],"is":[44,106],"either":[45],"sparse":[46],"(e.g.,":[47,60],"as":[48,90],"document-term":[50],"frequency":[51],"matrix)":[52],"or":[53,64],"only":[55],"few":[57],"hundred":[58],"dimensions":[59],"small":[62],"images":[63],"obtained":[66],"through":[67,123],"PCA).":[68],"show":[70],"such":[73,89],"cases,":[74],"can":[77],"be":[78],"implemented":[79],"solely":[80],"based":[81],"on":[82,85,135],"efficient":[83],"operations":[84],"matrix":[88],"elementwise":[91],"manipulation,":[92],"matrix-vector":[93],"multiplication":[94],"low-rank":[96],"SVD,":[97],"thus":[98],"entirely":[99],"avoiding":[100],"weight":[102],"matrix.":[103],"Our":[104],"simple":[107],"to":[108,111,116],"implement,":[109],"fast":[110],"run,":[112],"accurate":[113],"robust":[115],"outliers.":[117],"demonstrate":[119],"its":[120],"superior":[121],"performance":[122],"extensive":[124],"experiments":[125],"which":[126],"compare":[127],"our":[128],"with":[131],"plain":[133],"implementation":[134],"several":[136],"benchmark":[137],"sets.":[139]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}