{"id":"https://openalex.org/W4406459317","doi":"https://doi.org/10.1109/bigdata62323.2024.10825741","title":"Clustering and Topic Discovery of Multiway Data via Joint-NCMTF","display_name":"Clustering and Topic Discovery of Multiway Data via Joint-NCMTF","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406459317","doi":"https://doi.org/10.1109/bigdata62323.2024.10825741"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825741","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825741","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5082224254","display_name":"Benjamin Cobb","orcid":"https://orcid.org/0000-0002-3214-627X"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Benjamin Cobb","raw_affiliation_strings":["Georgia Institute of Technology,School of Computational Science and Engineering,Atlanta,GA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,School of Computational Science and Engineering,Atlanta,GA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071722225","display_name":"Ricardo A. Vel\u00e1squez","orcid":"https://orcid.org/0000-0002-7787-2275"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ricardo Velasquez","raw_affiliation_strings":["Georgia Institute of Technology,School of Computational Science and Engineering,Atlanta,GA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,School of Computational Science and Engineering,Atlanta,GA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016738770","display_name":"Richard Vuduc","orcid":"https://orcid.org/0000-0003-2178-138X"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Richard Vuduc","raw_affiliation_strings":["Georgia Institute of Technology,School of Computational Science and Engineering,Atlanta,GA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,School of Computational Science and Engineering,Atlanta,GA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101728710","display_name":"Haesun Park","orcid":"https://orcid.org/0000-0001-6259-7170"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haesun Park","raw_affiliation_strings":["Georgia Institute of Technology,School of Computational Science and Engineering,Atlanta,GA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,School of Computational Science and Engineering,Atlanta,GA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5082224254"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":0.8111,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.82945888,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1268","last_page":"1275"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9911999702453613,"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"}},{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9908999800682068,"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/computer-science","display_name":"Computer science","score":0.753457248210907},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7276814579963684},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5487523674964905},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46417853236198425},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44031086564064026},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3317776322364807},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08379799127578735}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.753457248210907},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7276814579963684},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5487523674964905},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46417853236198425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44031086564064026},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3317776322364807},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08379799127578735},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825741","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825741","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W343638764","https://openalex.org/W1504886279","https://openalex.org/W1547561528","https://openalex.org/W1632866817","https://openalex.org/W1758773383","https://openalex.org/W1921200167","https://openalex.org/W2009685860","https://openalex.org/W2022322548","https://openalex.org/W2024165284","https://openalex.org/W2071949631","https://openalex.org/W2093492509","https://openalex.org/W2113586398","https://openalex.org/W2117420919","https://openalex.org/W2124583124","https://openalex.org/W2138072998","https://openalex.org/W2144351558","https://openalex.org/W2144544802","https://openalex.org/W2144767994","https://openalex.org/W2440837865","https://openalex.org/W2482276862","https://openalex.org/W2538515886","https://openalex.org/W2559655401","https://openalex.org/W2600446419","https://openalex.org/W2754794949","https://openalex.org/W2773044566","https://openalex.org/W2788615138","https://openalex.org/W2890146511","https://openalex.org/W2898346288","https://openalex.org/W2956148206","https://openalex.org/W3169987204","https://openalex.org/W3186467619","https://openalex.org/W4235285603","https://openalex.org/W4306377799","https://openalex.org/W4327672421","https://openalex.org/W4381327470"],"related_works":["https://openalex.org/W4298130764","https://openalex.org/W2804364458","https://openalex.org/W2132641928","https://openalex.org/W4310225030","https://openalex.org/W2090259340","https://openalex.org/W1926736923","https://openalex.org/W1996130883","https://openalex.org/W2158836806","https://openalex.org/W2748574964","https://openalex.org/W2393816671"],"abstract_inverted_index":{"Nonnegative":[0,5,115],"Matrix":[1,7,117],"Factorization":[2,9,119],"(NMF)":[3],"and":[4,27,38,69,99,148,173,195],"Coupled":[6,116],"Tensor":[8,118],"(NCMTF)":[10],"are":[11,72],"Constrained":[12],"Low-Rank":[13],"Approximation":[14],"(CLRA)":[15],"models":[16],"which":[17,92,179],"have":[18,30],"found":[19],"use":[20],"in":[21,63,158],"many":[22],"applications.":[23],"In":[24],"particular,":[25],"NMF":[26,68,131,143],"its":[28,70],"variants":[29,71],"been":[31],"shown":[32],"to":[33,50,74],"produce":[34],"high-quality":[35],"soft":[36],"clustering":[37,47,98,172],"topic":[39,100,174,198],"modeling":[40,101,175,199],"results":[41,176],"with":[42],"the":[43,58,95,141,186],"property":[44],"that":[45],"each":[46,61],"assignment":[48],"relates":[49],"a":[51,64,108],"corresponding":[52],"topic;":[53],"thereby":[54],"providing":[55],"insight":[56],"into":[57],"nature":[59],"of":[60,103,112,122,140,155,188],"item":[62],"given":[65],"cluster.":[66],"However,":[67],"unable":[73],"process":[75],"heterogeneous":[76,124],"data":[77],"represented":[78],"as":[79,161],"one":[80],"or":[81],"more":[82],"coupled":[83,162],"tenors.":[84],"Similarly,":[85],"there":[86],"do":[87],"not":[88],"exist":[89],"tensorized":[90],"methods":[91,178],"fully":[93,128],"preserve":[94],"aforementioned":[96],"desirable":[97],"properties":[102],"NMF.":[104],"This":[105],"paper":[106],"develops":[107],"higher":[109,170],"order":[110],"analog":[111],"Joint-NMF,":[113],"Joint":[114],"(Joint-NCMTF),":[120],"capable":[121],"factorizing":[123],"tensor":[125],"datasets":[126,159],"whilst":[127],"preserving":[129],"these":[130],"properties.":[132],"To":[133],"accomplish":[134],"this,":[135],"we":[136],"develop":[137],"higher-order":[138,163],"analogs":[139],"entire":[142],"process,":[144],"including":[145],"crucial":[146],"pre":[147],"post-processing":[149],"steps.":[150],"By":[151],"incorporating":[152],"additional":[153],"dimensions":[154],"information":[156],"present":[157],"posed":[160],"tensors,":[164],"our":[165,189],"proposed":[166,190],"Joint-NCMTF":[167],"method":[168,191],"yields":[169],"quality":[171],"than":[177],"incorporate":[180],"less":[181],"information.":[182],"We":[183],"empirically":[184],"demonstrate":[185],"effectiveness":[187],"on":[192],"multiple":[193],"synthetic":[194],"two":[196],"real-world":[197],"tasks.":[200]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}