{"id":"https://openalex.org/W4399418386","doi":"https://doi.org/10.1145/3652583.3658042","title":"Subspace Clustering with A Hybrid Adaptive Graph Filter","display_name":"Subspace Clustering with A Hybrid Adaptive Graph Filter","publication_year":2024,"publication_date":"2024-05-30","ids":{"openalex":"https://openalex.org/W4399418386","doi":"https://doi.org/10.1145/3652583.3658042"},"language":"en","primary_location":{"id":"doi:10.1145/3652583.3658042","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3652583.3658042","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3658042","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3658042","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012555900","display_name":"Lai Wei","orcid":"https://orcid.org/0000-0002-6116-1671"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lai Wei","raw_affiliation_strings":["College of Information Engineering, Shanghai Maritime University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-6116-1671","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shanghai Maritime University, Shanghai, China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5099043532","display_name":"Mingyuan Xi","orcid":"https://orcid.org/0009-0008-5824-4522"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingyuan Xi","raw_affiliation_strings":["College of Information Engineering, Shanghai Maritime University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0008-5824-4522","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shanghai Maritime University, Shanghai, China","institution_ids":["https://openalex.org/I96733725"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5012555900"],"corresponding_institution_ids":["https://openalex.org/I96733725"],"apc_list":null,"apc_paid":null,"fwci":0.6623,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.73204165,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1070","last_page":"1078"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9980999827384949,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9980999827384949,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9961000084877014,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9656999707221985,"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/cluster-analysis","display_name":"Cluster analysis","score":0.5929752588272095},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.5192154049873352},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5039750933647156},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.48626697063446045},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4724704921245575},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.45316141843795776},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.44151875376701355},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.43742120265960693},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4371337592601776},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.42564743757247925},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41888123750686646},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.4169125556945801},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3639345169067383},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1281116008758545},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.10000821948051453}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5929752588272095},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.5192154049873352},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5039750933647156},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.48626697063446045},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4724704921245575},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.45316141843795776},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.44151875376701355},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.43742120265960693},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4371337592601776},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.42564743757247925},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41888123750686646},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.4169125556945801},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3639345169067383},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1281116008758545},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.10000821948051453},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3652583.3658042","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3652583.3658042","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3658042","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3652583.3658042","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3652583.3658042","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3658042","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4399418386.pdf"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1600471557","https://openalex.org/W1981458038","https://openalex.org/W1993962865","https://openalex.org/W1997201895","https://openalex.org/W2119227770","https://openalex.org/W2121947440","https://openalex.org/W2122712590","https://openalex.org/W2125874614","https://openalex.org/W2150414161","https://openalex.org/W2160616617","https://openalex.org/W2164931791","https://openalex.org/W2177347332","https://openalex.org/W2187089797","https://openalex.org/W2195250169","https://openalex.org/W2560674852","https://openalex.org/W2592249290","https://openalex.org/W2725281289","https://openalex.org/W2747329762","https://openalex.org/W2798534672","https://openalex.org/W2963165461","https://openalex.org/W2966502719","https://openalex.org/W2979685515","https://openalex.org/W2990138404","https://openalex.org/W2994560339","https://openalex.org/W3019954098","https://openalex.org/W3043476515","https://openalex.org/W3092947908","https://openalex.org/W3098561772","https://openalex.org/W3103988127","https://openalex.org/W3112881158","https://openalex.org/W3143649444","https://openalex.org/W3165527726","https://openalex.org/W3189403855","https://openalex.org/W4225825060","https://openalex.org/W4386083044","https://openalex.org/W6601365666","https://openalex.org/W6799528744"],"related_works":["https://openalex.org/W3100286349","https://openalex.org/W2896134808","https://openalex.org/W4289378085","https://openalex.org/W4294291164","https://openalex.org/W3172436493","https://openalex.org/W1887135636","https://openalex.org/W4287164812","https://openalex.org/W2386063599","https://openalex.org/W1975884855","https://openalex.org/W3213150849"],"abstract_inverted_index":{"Subspace":[0],"clustering":[1,22,135],"is":[2,65,154],"a":[3,43,48,60,69,74],"powerful":[4],"tool":[5],"for":[6,67,76],"grouping":[7],"data":[8],"samples":[9],"into":[10,59],"their":[11],"underlying":[12],"subspaces.":[13],"In":[14],"this":[15],"paper,":[16],"we":[17],"propose":[18],"an":[19],"advanced":[20],"subspace":[21,134],"algorithm":[23],"called":[24],"SCHAGF":[25,34,140,152],"(Subspace":[26],"Clustering":[27],"with":[28],"A":[29],"Hybrid":[30],"Adaptive":[31],"Graph":[32],"Filter).":[33],"leverages":[35],"the":[36,77,82,87,101,105,118,123,127,139,142,148],"obtained":[37],"reconstruction":[38,78,128],"coefficient":[39,79,88,129],"matrix":[40,89],"to":[41,93,156],"design":[42],"low-pass":[44],"graph":[45,50,54,62,84,107],"filter":[46,51,85,108],"and":[47,73,86,113],"high-pass":[49],"simultaneously.":[52],"These":[53],"filters":[55],"are":[56,90],"then":[57],"integrated":[58],"hybrid":[61,83,106],"filter,":[63],"which":[64],"used":[66],"designing":[68],"feature":[70],"extraction":[71],"function":[72],"constraint":[75],"matrix.":[80,130],"Then":[81],"iteratively":[91],"updated":[92],"achieve":[94],"optimal":[95],"values.":[96],"Our":[97],"results":[98],"demonstrate":[99],"that":[100,138],"features":[102],"extracted":[103],"using":[104],"exhibit":[109],"compactness":[110],"within":[111],"classes":[112],"discrimination":[114],"between":[115],"classes.":[116],"Additionally,":[117],"new":[119],"constraints":[120],"significantly":[121],"enhance":[122],"block-diagonal":[124],"structure":[125],"of":[126,133],"Finally,":[131],"plenty":[132],"experiments":[136],"show":[137],"outperforms":[141],"related":[143],"algorithms.":[144],"Moreover,":[145],"by":[146],"incorporating":[147],"thresholding":[149,151],"technique,":[150],"(TSCHAGF)":[153],"found":[155],"surpass":[157],"some":[158],"deep":[159],"models.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
