{"id":"https://openalex.org/W4404132889","doi":"https://doi.org/10.1109/thms.2024.3483848","title":"Multidimensional Scaling Orienting Discriminative Co-Representation Learning","display_name":"Multidimensional Scaling Orienting Discriminative Co-Representation Learning","publication_year":2024,"publication_date":"2024-11-07","ids":{"openalex":"https://openalex.org/W4404132889","doi":"https://doi.org/10.1109/thms.2024.3483848"},"language":"en","primary_location":{"id":"doi:10.1109/thms.2024.3483848","is_oa":false,"landing_page_url":"https://doi.org/10.1109/thms.2024.3483848","pdf_url":null,"source":{"id":"https://openalex.org/S2476799526","display_name":"IEEE Transactions on Human-Machine Systems","issn_l":"2168-2291","issn":["2168-2291","2168-2305"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Human-Machine Systems","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/A5038733949","display_name":"Zhang Qin","orcid":"https://orcid.org/0009-0005-2161-0742"},"institutions":[{"id":"https://openalex.org/I154341788","display_name":"Tangshan College","ror":"https://ror.org/00rfn0469","country_code":"CN","type":"education","lineage":["https://openalex.org/I154341788"]},{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhang Qin","raw_affiliation_strings":["Tangshan Research Institute, Southwest Jiaotong University, Tangshan, China"],"affiliations":[{"raw_affiliation_string":"Tangshan Research Institute, Southwest Jiaotong University, Tangshan, China","institution_ids":["https://openalex.org/I154341788","https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100629236","display_name":"Yinghui Zhang","orcid":"https://orcid.org/0000-0002-3435-5649"},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]},{"id":"https://openalex.org/I4400573292","display_name":"Chengdu Neusoft University","ror":"https://ror.org/04p9p1r69","country_code":null,"type":"education","lineage":["https://openalex.org/I4400573292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinghui Zhang","raw_affiliation_strings":["Chengdu Neusoft University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Chengdu Neusoft University, Chengdu, China","institution_ids":["https://openalex.org/I4210134419","https://openalex.org/I4400573292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100357108","display_name":"Hongjun Wang","orcid":"https://orcid.org/0000-0001-7280-2852"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongjun Wang","raw_affiliation_strings":["School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076976899","display_name":"Zhipeng Luo","orcid":"https://orcid.org/0000-0002-4053-5443"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhipeng Luo","raw_affiliation_strings":["School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032769556","display_name":"Chongshou Li","orcid":"https://orcid.org/0000-0002-7595-0997"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chongshou Li","raw_affiliation_strings":["School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070559820","display_name":"Tianrui Li","orcid":"https://orcid.org/0000-0001-7780-104X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianrui Li","raw_affiliation_strings":["School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5038733949"],"corresponding_institution_ids":["https://openalex.org/I154341788","https://openalex.org/I4800084"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17700228,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"55","issue":"1","first_page":"71","last_page":"82"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.6320000290870667,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.6320000290870667,"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/T14222","display_name":"Knowledge Management and Technology","score":0.5503000020980835,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7979235053062439},{"id":"https://openalex.org/keywords/multidimensional-scaling","display_name":"Multidimensional scaling","score":0.6686404943466187},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6639091968536377},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.6484339237213135},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5024268627166748},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4636823534965515},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.46288204193115234},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.4337167739868164},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.320163756608963},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26208680868148804},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23934432864189148},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.08712401986122131},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.052365005016326904}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7979235053062439},{"id":"https://openalex.org/C91682802","wikidata":"https://www.wikidata.org/wiki/Q620538","display_name":"Multidimensional scaling","level":2,"score":0.6686404943466187},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6639091968536377},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.6484339237213135},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5024268627166748},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4636823534965515},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.46288204193115234},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.4337167739868164},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.320163756608963},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26208680868148804},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23934432864189148},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.08712401986122131},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.052365005016326904},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/thms.2024.3483848","is_oa":false,"landing_page_url":"https://doi.org/10.1109/thms.2024.3483848","pdf_url":null,"source":{"id":"https://openalex.org/S2476799526","display_name":"IEEE Transactions on Human-Machine Systems","issn_l":"2168-2291","issn":["2168-2291","2168-2305"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Human-Machine Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.8100000023841858}],"awards":[{"id":"https://openalex.org/G4115684213","display_name":null,"funder_award_id":"62176221","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8063415298","display_name":null,"funder_award_id":"62276216","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W763930222","https://openalex.org/W1981472895","https://openalex.org/W1993436046","https://openalex.org/W1995450389","https://openalex.org/W2000215628","https://openalex.org/W2001141328","https://openalex.org/W2001619934","https://openalex.org/W2006255103","https://openalex.org/W2057923756","https://openalex.org/W2058240487","https://openalex.org/W2077139171","https://openalex.org/W2097308346","https://openalex.org/W2098578926","https://openalex.org/W2133576408","https://openalex.org/W2137758646","https://openalex.org/W2163922914","https://openalex.org/W2169507824","https://openalex.org/W2169528473","https://openalex.org/W2181139552","https://openalex.org/W2294798173","https://openalex.org/W2320035791","https://openalex.org/W2802762625","https://openalex.org/W2804721500","https://openalex.org/W2922527181","https://openalex.org/W2993529567","https://openalex.org/W2998352741","https://openalex.org/W3009065419","https://openalex.org/W3019448917","https://openalex.org/W3020993372","https://openalex.org/W3023843563","https://openalex.org/W3024024928","https://openalex.org/W3097526925","https://openalex.org/W3114371502","https://openalex.org/W3126424245","https://openalex.org/W3131105487","https://openalex.org/W3155561834","https://openalex.org/W3160724798","https://openalex.org/W3174971746","https://openalex.org/W3178302783","https://openalex.org/W4206500677","https://openalex.org/W4206622711","https://openalex.org/W4210273945","https://openalex.org/W4210768739","https://openalex.org/W4214831569","https://openalex.org/W4220682630","https://openalex.org/W4229023628","https://openalex.org/W4285327361","https://openalex.org/W4288064702","https://openalex.org/W4294012891","https://openalex.org/W4294237762","https://openalex.org/W4295767881","https://openalex.org/W4301393088","https://openalex.org/W4304014904","https://openalex.org/W4312298503","https://openalex.org/W4312440891","https://openalex.org/W4319444044","https://openalex.org/W4321458299","https://openalex.org/W4360770820","https://openalex.org/W4386321924","https://openalex.org/W4392815369","https://openalex.org/W6754918841","https://openalex.org/W6861486676"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W4241372895"],"abstract_inverted_index":{"Co-representation,":[0],"which":[1,204],"co-represents":[2],"samples":[3,34,123],"and":[4,22,35,57,124,136,191,201],"features,":[5,36],"has":[6],"been":[7],"widely":[8],"used":[9],"in":[10,64,174],"various":[11],"machine":[12],"learning":[13,82,98],"tasks,":[14],"such":[15,61],"as":[16,51],"document":[17],"clustering,":[18],"gene":[19],"expression":[20],"analysis,":[21],"recommendation":[23],"systems.":[24],"It":[25],"not":[26],"only":[27],"reveals":[28,39],"the":[29,40,52,102,110,119,132,148,161,180,192],"cluster":[30],"structure":[31],"of":[32,55,118,134,182],"both":[33,199],"but":[37],"also":[38],"sample\u2013feature":[41],"correlation.":[42],"Given":[43],"a":[44,96,108,170,175],"tabular":[45],"data":[46,67],"matrix,":[47],"co-representation":[48,81,97,111,173],"usually":[49],"exhibits":[50],"co-occurrence":[53,105],"structures":[54],"rows":[56],"columns.":[58],"However,":[59],"identifying":[60],"structured":[62],"patterns":[63],"complex":[65,140],"real-world":[66,141],"can":[68,158,197],"be":[69],"very":[70],"challenging.":[71],"To":[72,178],"address":[73],"this":[74],"problem,":[75],"we":[76,152,184],"propose":[77],"an":[78],"unsupervised":[79],"discriminative":[80,202],"model":[83],"based":[84],"on":[85,188],"multidimensional":[86],"scaling":[87],"(DCLMDS).":[88],"The":[89],"main":[90],"novelty":[91],"is":[92],"that":[93,157,195],"DCLMDS":[94,114,167,196],"introduces":[95],"term":[99],"to":[100,168],"ensure":[101],"discriminability":[103],"between":[104,122],"structures.":[106],"As":[107],"result,":[109],"learned":[112],"by":[113,147],"contains":[115],"richer":[116],"information":[117,142],"underlying":[120],"correlation":[121],"features":[125],"within":[126,163],"data.":[127],"This":[128],"could":[129],"subsequently":[130],"enhance":[131],"capacity":[133],"machines":[135],"systems":[137],"for":[138],"processing":[139],"more":[143,171],"proficiently.":[144],"Furthermore,":[145],"inspired":[146],"fuzzy":[149,154],"set":[150],"theory,":[151],"integrate":[153],"membership":[155],"degree":[156],"accurately":[159],"capture":[160],"uncertainty":[162],"data,":[164],"thus":[165],"enabling":[166],"learn":[169],"effective":[172],"soft":[176],"manner.":[177],"evaluate":[179],"performance":[181],"DCLMDS,":[183],"conduct":[185],"extensive":[186],"experiments":[187],"18":[189],"datasets,":[190],"results":[193],"demonstrate":[194],"generate":[198],"accurate":[200],"co-representation,":[203],"well":[205],"meets":[206],"our":[207],"desired":[208],"outcomes.":[209]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
