{"id":"https://openalex.org/W3100923960","doi":"https://doi.org/10.1109/tbdata.2020.3039036","title":"Regularized Spectral Clustering With Entropy Perturbation","display_name":"Regularized Spectral Clustering With Entropy Perturbation","publication_year":2020,"publication_date":"2020-11-18","ids":{"openalex":"https://openalex.org/W3100923960","doi":"https://doi.org/10.1109/tbdata.2020.3039036","mag":"3100923960"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2020.3039036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2020.3039036","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-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/A5101902089","display_name":"Xiao Hu","orcid":"https://orcid.org/0000-0002-8268-0040"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiao Hu","raw_affiliation_strings":["Mianyang Big data and knowledge engineering laboratory, SouthWest University of Science and Technology, Mianyang, China"],"affiliations":[{"raw_affiliation_string":"Mianyang Big data and knowledge engineering laboratory, SouthWest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053489571","display_name":"Hui Zhang","orcid":"https://orcid.org/0000-0003-2442-0045"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Zhang","raw_affiliation_strings":["Computer Science and Technology, Southwest University of Science and Technology, Mianyang, Sichuan, China"],"affiliations":[{"raw_affiliation_string":"Computer Science and Technology, Southwest University of Science and Technology, Mianyang, Sichuan, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102956351","display_name":"Chunming Yang","orcid":"https://orcid.org/0000-0002-3035-4980"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"ChunMing Yang","raw_affiliation_strings":["Mianyang Big data and knowledge engineering laboratory, SouthWest University of Science and Technology, Mianyang, China"],"affiliations":[{"raw_affiliation_string":"Mianyang Big data and knowledge engineering laboratory, SouthWest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101594946","display_name":"Xujian Zhao","orcid":"https://orcid.org/0000-0003-4717-9231"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"XuJian Zhao","raw_affiliation_strings":["Computer Science and Technology, Southwest University of Science and Technology, Mianyang, Sichuan, China"],"affiliations":[{"raw_affiliation_string":"Computer Science and Technology, Southwest University of Science and Technology, Mianyang, Sichuan, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065955866","display_name":"Bo Li","orcid":"https://orcid.org/0000-0002-9772-4317"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Li","raw_affiliation_strings":["Mianyang Big data and knowledge engineering laboratory, SouthWest University of Science and Technology, Mianyang, China"],"affiliations":[{"raw_affiliation_string":"Mianyang Big data and knowledge engineering laboratory, SouthWest University of Science and Technology, Mianyang, China","institution_ids":["https://openalex.org/I1297991670"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101902089"],"corresponding_institution_ids":["https://openalex.org/I1297991670"],"apc_list":null,"apc_paid":null,"fwci":0.4885,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.66594407,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"7","issue":"6","first_page":"967","last_page":"972"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9973999857902527,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9973999857902527,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9853000044822693,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/cluster-analysis","display_name":"Cluster analysis","score":0.7124424576759338},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.631197452545166},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.6231688261032104},{"id":"https://openalex.org/keywords/perturbation","display_name":"Perturbation (astronomy)","score":0.5475517511367798},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.48129358887672424},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.465542197227478},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45216265320777893},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.44014987349510193},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.41824597120285034},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4112614095211029},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3969508707523346},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2635239064693451},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.22613325715065002}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7124424576759338},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.631197452545166},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.6231688261032104},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.5475517511367798},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.48129358887672424},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.465542197227478},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45216265320777893},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.44014987349510193},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.41824597120285034},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4112614095211029},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3969508707523346},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2635239064693451},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.22613325715065002},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbdata.2020.3039036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2020.3039036","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W857387926","https://openalex.org/W1973207991","https://openalex.org/W2023655578","https://openalex.org/W2044433757","https://openalex.org/W2048119540","https://openalex.org/W2102158416","https://openalex.org/W2102907934","https://openalex.org/W2107887685","https://openalex.org/W2118527389","https://openalex.org/W2132914434","https://openalex.org/W2146670837","https://openalex.org/W2153922613","https://openalex.org/W2165874743","https://openalex.org/W2174754147","https://openalex.org/W2396461274","https://openalex.org/W2805332017","https://openalex.org/W2962967173","https://openalex.org/W3101919829","https://openalex.org/W6623753063","https://openalex.org/W6675424377","https://openalex.org/W6675939294","https://openalex.org/W6676180653","https://openalex.org/W6684578312","https://openalex.org/W6726458226","https://openalex.org/W6751664678"],"related_works":["https://openalex.org/W4296209631","https://openalex.org/W2561617217","https://openalex.org/W2025378473","https://openalex.org/W2355801475","https://openalex.org/W4206659427","https://openalex.org/W2170062176","https://openalex.org/W2148135840","https://openalex.org/W106004901","https://openalex.org/W2973622563","https://openalex.org/W2316648939"],"abstract_inverted_index":{"Spectral":[0],"clustering":[1,5,30,61,152],"is":[2,22,38,63,129,139],"a":[3,10,55,57,88,116,134],"popular":[4],"method":[6,62],"because":[7],"it":[8,37],"gives":[9],"natural":[11],"way":[12],"to":[13,40,92,101,109,123],"reduce":[14],"the":[15,26,43,71,82,94,98,102,107,111,125,131],"dimensionality":[16],"of":[17,28,115],"data":[18,112],"using":[19],"eigenvectors.":[20],"It":[21],"well":[23],"known":[24],"that":[25,81,144],"performance":[27,149],"spectral":[29,60,151],"could":[31],"be":[32,85,106],"improved":[33],"via":[34],"regularization.":[35],"Nevertheless,":[36],"hard":[39],"cope":[41],"with":[42],"different":[44],"cases":[45],"by":[46],"only":[47],"one":[48],"constant":[49,117],"regularization":[50,108,118],"parameter.":[51,119],"To":[52],"solve":[53],"such":[54],"problem,":[56],"novel":[58],"regularized":[59],"proposed.":[64],"Specifically,":[65],"two":[66],"modules":[67],"are":[68],"integrated":[69],"in":[70,121],"proposed":[72],"method.":[73],"First,":[74],"under":[75],"matrix":[76,113],"perturbation":[77,126,135],"analysis,":[78],"we":[79],"prove":[80],"entropy":[83,104],"can":[84],"used":[86],"as":[87],"rank":[89],"score":[90],"function":[91],"reveal":[93],"informative":[95],"eigenvector,":[96],"and":[97,153],"eigenvector":[99],"corresponding":[100],"minimal":[103],"will":[105],"regularize":[110],"instead":[114],"Second,":[120],"order":[122],"ensure":[124],"on":[127,137],"eigenspace":[128],"within":[130],"effective":[132],"range,":[133],"boundary":[136],"eigenvectors":[138],"given.":[140],"Numerical":[141],"results":[142],"showed":[143],"our":[145],"proposal":[146],"has":[147],"superior":[148],"than":[150],"k-means":[154],"algorithm.":[155]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}