{"id":"https://openalex.org/W4401864395","doi":"https://doi.org/10.1145/3637528.3671839","title":"QGRL: Quaternion Graph Representation Learning for Heterogeneous Feature Data Clustering","display_name":"QGRL: Quaternion Graph Representation Learning for Heterogeneous Feature Data Clustering","publication_year":2024,"publication_date":"2024-08-24","ids":{"openalex":"https://openalex.org/W4401864395","doi":"https://doi.org/10.1145/3637528.3671839"},"language":"en","primary_location":{"id":"doi:10.1145/3637528.3671839","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671839","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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/A5100713117","display_name":"Junyang Chen","orcid":"https://orcid.org/0009-0002-4724-1090"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junyang Chen","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016989631","display_name":"Yuzhu Ji","orcid":"https://orcid.org/0000-0003-3589-3884"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuzhu Ji","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101349882","display_name":"Rong Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Rong Zou","raw_affiliation_strings":["Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100329232","display_name":"Yiqun Zhang","orcid":"https://orcid.org/0000-0002-0328-987X"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiqun Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038516431","display_name":"Yiu\u2010ming Cheung","orcid":"https://orcid.org/0000-0001-7629-4648"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yiu-ming Cheung","raw_affiliation_strings":["Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China","institution_ids":["https://openalex.org/I141568987"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100713117"],"corresponding_institution_ids":["https://openalex.org/I139024713"],"apc_list":null,"apc_paid":null,"fwci":5.3903,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.96230455,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"297","last_page":"306"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.998199999332428,"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":0.998199999332428,"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":0.9944999814033508,"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/computer-science","display_name":"Computer science","score":0.7282537221908569},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7183254957199097},{"id":"https://openalex.org/keywords/quaternion","display_name":"Quaternion","score":0.6400727033615112},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5717778205871582},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5401140451431274},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5240083932876587},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4893724322319031},{"id":"https://openalex.org/keywords/external-data-representation","display_name":"External Data Representation","score":0.46425682306289673},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.408985435962677},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2805536389350891},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1872023344039917}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7282537221908569},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7183254957199097},{"id":"https://openalex.org/C200127275","wikidata":"https://www.wikidata.org/wiki/Q173853","display_name":"Quaternion","level":2,"score":0.6400727033615112},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5717778205871582},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5401140451431274},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5240083932876587},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4893724322319031},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.46425682306289673},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.408985435962677},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2805536389350891},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1872023344039917},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3637528.3671839","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671839","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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":40,"referenced_works":["https://openalex.org/W593633726","https://openalex.org/W1605406256","https://openalex.org/W2020344074","https://openalex.org/W2025768430","https://openalex.org/W2047878524","https://openalex.org/W2132149726","https://openalex.org/W2132914434","https://openalex.org/W2148425841","https://openalex.org/W2187089797","https://openalex.org/W2338257905","https://openalex.org/W2473552888","https://openalex.org/W2808409763","https://openalex.org/W2894977338","https://openalex.org/W2895388200","https://openalex.org/W2900404321","https://openalex.org/W2905556235","https://openalex.org/W2909504023","https://openalex.org/W2914304175","https://openalex.org/W2925162041","https://openalex.org/W2963719423","https://openalex.org/W2964732194","https://openalex.org/W2966878259","https://openalex.org/W2997152122","https://openalex.org/W2997546679","https://openalex.org/W3004946360","https://openalex.org/W3017786722","https://openalex.org/W3043922872","https://openalex.org/W3081465174","https://openalex.org/W3101709902","https://openalex.org/W3128396846","https://openalex.org/W3136526008","https://openalex.org/W3173294575","https://openalex.org/W3185513611","https://openalex.org/W3212924718","https://openalex.org/W4206441147","https://openalex.org/W4225674624","https://openalex.org/W4285601133","https://openalex.org/W4295308409","https://openalex.org/W4312248562","https://openalex.org/W4382318469"],"related_works":["https://openalex.org/W2952512863","https://openalex.org/W4285218279","https://openalex.org/W3134504629","https://openalex.org/W2938696877","https://openalex.org/W4323911413","https://openalex.org/W1982536061","https://openalex.org/W4210631502","https://openalex.org/W4286796787","https://openalex.org/W2952582877","https://openalex.org/W3170043432"],"abstract_inverted_index":{"Clustering":[0],"is":[1,121,196],"one":[2],"of":[3,20,63,79,105,136,153,164,175,185,188],"the":[4,30,33,72,77,102,125,134,141,145,154,162,165],"most":[5],"commonly":[6],"used":[7],"techniques":[8],"for":[9,81],"unsupervised":[10,82],"data":[11,15,108,126,182],"analysis.":[12],"As":[13],"real":[14],"sets":[16,183],"are":[17,26],"usually":[18],"composed":[19,184],"numerical":[21,189],"and":[22,36,156,178,190],"categorical":[23,191],"features":[24,65],"that":[25,93,101],"heterogeneous":[27,83,106],"in":[28,32,58,95,173],"nature,":[29],"heterogeneity":[31],"distance":[34],"metric":[35],"feature":[37,84,107],"coupling":[38,118],"prevents":[39],"deep":[40,90],"representation":[41,85,114,155],"learning":[42,60],"from":[43,66,71],"achieving":[44],"satisfactory":[45],"clustering":[46,142,176],"accuracy.":[47],"Currently,":[48],"supervised":[49],"Quaternion":[50,167],"Representation":[51,169],"Learning":[52,170],"(QRL)":[53],"has":[54],"achieved":[55],"remarkable":[56],"success":[57],"efficiently":[59],"informative":[61],"representations":[62],"coupled":[64],"multiple":[67],"views":[68],"derived":[69],"endogenously":[70],"original":[73],"data.":[74],"To":[75,99],"inherit":[76],"advantages":[78],"QRL":[80,91],"learning,":[86,115],"we":[87],"propose":[88],"a":[89,116,150],"model":[92,146],"works":[94],"an":[96,129],"encoder-decoder":[97],"manner.":[98],"ensure":[100],"implicit":[103],"couplings":[104],"can":[109],"be":[110,133],"well":[111],"characterized":[112],"by":[113],"hierarchical":[117],"encoding":[119],"strategy":[120],"designed":[122],"to":[123,132,148,180],"convert":[124],"set":[127],"into":[128,144],"attributed":[130],"graph":[131],"input":[135],"QRL.":[137],"We":[138],"also":[139],"integrate":[140],"objective":[143],"training":[147],"facilitate":[149],"joint":[151],"optimization":[152],"clustering.":[157],"Extensive":[158],"experimental":[159],"evaluations":[160],"illustrate":[161],"superiority":[163],"proposed":[166],"Graph":[168],"(QGRL)":[171],"method":[172],"terms":[174],"accuracy":[177],"robustness":[179],"various":[181],"arbitrary":[186],"combinations":[187],"features.":[192],"The":[193],"source":[194],"code":[195],"opened":[197],"at":[198],"https://github.com/Juny-Chen/QGRL.git.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":4}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}