{"id":"https://openalex.org/W4408969590","doi":"https://doi.org/10.1007/s00357-025-09500-x","title":"A Novel Approach for Biclustering Bipartite Networks: An Extension of Finite Mixtures of Latent Trait Analyzers","display_name":"A Novel Approach for Biclustering Bipartite Networks: An Extension of Finite Mixtures of Latent Trait Analyzers","publication_year":2025,"publication_date":"2025-03-26","ids":{"openalex":"https://openalex.org/W4408969590","doi":"https://doi.org/10.1007/s00357-025-09500-x"},"language":"en","primary_location":{"id":"doi:10.1007/s00357-025-09500-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00357-025-09500-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00357-025-09500-x.pdf","source":{"id":"https://openalex.org/S73028643","display_name":"Journal of Classification","issn_l":"0176-4268","issn":["0176-4268","1432-1343"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Classification","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s00357-025-09500-x.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093227493","display_name":"Dalila Failli","orcid":"https://orcid.org/0000-0003-3234-2964"},"institutions":[{"id":"https://openalex.org/I27483092","display_name":"University of Perugia","ror":"https://ror.org/00x27da85","country_code":"IT","type":"education","lineage":["https://openalex.org/I27483092"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Dalila Failli","raw_affiliation_strings":["Dipartimento di Scienze Politiche, Universit\u00e0 degli Studi di Perugia, Via Pascoli 20, Perugia, 06123, Italy"],"raw_orcid":"https://orcid.org/0000-0003-3234-2964","affiliations":[{"raw_affiliation_string":"Dipartimento di Scienze Politiche, Universit\u00e0 degli Studi di Perugia, Via Pascoli 20, Perugia, 06123, Italy","institution_ids":["https://openalex.org/I27483092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044999410","display_name":"Maria Francesca Marino","orcid":"https://orcid.org/0000-0002-5841-7613"},"institutions":[{"id":"https://openalex.org/I45084792","display_name":"University of Florence","ror":"https://ror.org/04jr1s763","country_code":"IT","type":"education","lineage":["https://openalex.org/I45084792"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Maria Francesca Marino","raw_affiliation_strings":["Dipartimento di Statistica, Informatica, Applicazioni, Universit\u00e0 degli Studi di Firenze, Viale Morgagni 59, Firenze, 50134, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dipartimento di Statistica, Informatica, Applicazioni, Universit\u00e0 degli Studi di Firenze, Viale Morgagni 59, Firenze, 50134, Italy","institution_ids":["https://openalex.org/I45084792"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088400471","display_name":"Francesca Martella","orcid":"https://orcid.org/0000-0001-9295-8598"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesca Martella","raw_affiliation_strings":["Dipartimento di Scienze Statistiche, Sapienza Universit\u00e0 di Roma, Piazzale Aldo Moro 5, Roma, 00185, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dipartimento di Scienze Statistiche, Sapienza Universit\u00e0 di Roma, Piazzale Aldo Moro 5, Roma, 00185, Italy","institution_ids":["https://openalex.org/I861853513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5093227493"],"corresponding_institution_ids":["https://openalex.org/I27483092"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":2.9051,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.8894538,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"42","issue":"3","first_page":"492","last_page":"516"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9901000261306763,"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":0.9901000261306763,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9824000000953674,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9797000288963318,"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/biclustering","display_name":"Biclustering","score":0.8080861568450928},{"id":"https://openalex.org/keywords/extension","display_name":"Extension (predicate logic)","score":0.7482881546020508},{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.7421896457672119},{"id":"https://openalex.org/keywords/trait","display_name":"Trait","score":0.6024810075759888},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.49598583579063416},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4206191301345825},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3971301019191742},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37128889560699463},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3436516523361206},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.28119874000549316},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.272175669670105},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.1117943823337555}],"concepts":[{"id":"https://openalex.org/C144817290","wikidata":"https://www.wikidata.org/wiki/Q2976575","display_name":"Biclustering","level":5,"score":0.8080861568450928},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.7482881546020508},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.7421896457672119},{"id":"https://openalex.org/C106934330","wikidata":"https://www.wikidata.org/wiki/Q1971873","display_name":"Trait","level":2,"score":0.6024810075759888},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.49598583579063416},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4206191301345825},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3971301019191742},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37128889560699463},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3436516523361206},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.28119874000549316},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.272175669670105},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.1117943823337555},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s00357-025-09500-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00357-025-09500-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00357-025-09500-x.pdf","source":{"id":"https://openalex.org/S73028643","display_name":"Journal of Classification","issn_l":"0176-4268","issn":["0176-4268","1432-1343"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Classification","raw_type":"journal-article"},{"id":"pmh:oai:flore.unifi.it:2158/1430873","is_oa":true,"landing_page_url":"https://hdl.handle.net/2158/1430873","pdf_url":null,"source":{"id":"https://openalex.org/S4306402033","display_name":"Florence Research (University of Florence)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45084792","host_organization_name":"University of Florence","host_organization_lineage":["https://openalex.org/I45084792"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:iris.uniroma1.it:11573/1738521","is_oa":false,"landing_page_url":"https://hdl.handle.net/11573/1738521","pdf_url":null,"source":{"id":"https://openalex.org/S4377196107","display_name":"IRIS Research product catalog (Sapienza University of Rome)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s00357-025-09500-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00357-025-09500-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00357-025-09500-x.pdf","source":{"id":"https://openalex.org/S73028643","display_name":"Journal of Classification","issn_l":"0176-4268","issn":["0176-4268","1432-1343"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Classification","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2425038180","display_name":null,"funder_award_id":"FSE REACT-EU 2022-2024","funder_id":"https://openalex.org/F4320331528","funder_display_name":"Ministero dell'Universit\u00e0 e della Ricerca"},{"id":"https://openalex.org/G4608343571","display_name":null,"funder_award_id":"Dipartimenti Eccellenti 2018-2022","funder_id":"https://openalex.org/F4320331528","funder_display_name":"Ministero dell'Universit\u00e0 e della Ricerca"},{"id":"https://openalex.org/G5797095062","display_name":null,"funder_award_id":"Dipartimenti Eccellenti 2023-2027","funder_id":"https://openalex.org/F4320331528","funder_display_name":"Ministero dell'Universit\u00e0 e della Ricerca"}],"funders":[{"id":"https://openalex.org/F4320322510","display_name":"Sapienza Universit\u00e0 di Roma","ror":"https://ror.org/02be6w209"},{"id":"https://openalex.org/F4320326523","display_name":"Universit\u00e0 degli Studi di Perugia","ror":"https://ror.org/00x27da85"},{"id":"https://openalex.org/F4320331528","display_name":"Ministero dell'Universit\u00e0 e della Ricerca","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4408969590.pdf"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W1694128711","https://openalex.org/W1743991736","https://openalex.org/W1966402429","https://openalex.org/W1967495697","https://openalex.org/W1982509351","https://openalex.org/W1984007049","https://openalex.org/W1987399558","https://openalex.org/W1992149151","https://openalex.org/W2024353935","https://openalex.org/W2029761439","https://openalex.org/W2047201701","https://openalex.org/W2049500688","https://openalex.org/W2049633694","https://openalex.org/W2080295262","https://openalex.org/W2089559915","https://openalex.org/W2096091969","https://openalex.org/W2102907934","https://openalex.org/W2108818539","https://openalex.org/W2109820980","https://openalex.org/W2114244473","https://openalex.org/W2115881827","https://openalex.org/W2125183960","https://openalex.org/W2133095386","https://openalex.org/W2144799688","https://openalex.org/W2168175751","https://openalex.org/W2330302092","https://openalex.org/W2470943894","https://openalex.org/W2488678869","https://openalex.org/W2554987453","https://openalex.org/W2582743722","https://openalex.org/W2613294715","https://openalex.org/W2789311406","https://openalex.org/W2796491734","https://openalex.org/W2944738630","https://openalex.org/W4210981077","https://openalex.org/W4212863985","https://openalex.org/W4235169531","https://openalex.org/W4241635929","https://openalex.org/W4388759420","https://openalex.org/W4393444002","https://openalex.org/W4398778561","https://openalex.org/W4404693264","https://openalex.org/W6629510986","https://openalex.org/W6785544989","https://openalex.org/W6804735368","https://openalex.org/W7020380774"],"related_works":["https://openalex.org/W1974340769","https://openalex.org/W2900595096","https://openalex.org/W4289277241","https://openalex.org/W2979322793","https://openalex.org/W2765801824","https://openalex.org/W2188068678","https://openalex.org/W2157302779","https://openalex.org/W4236723217","https://openalex.org/W2592285132","https://openalex.org/W2795952052"],"abstract_inverted_index":{"Abstract":[0],"In":[1,28,67,85],"the":[2,33,52,64,104,121,131,143,171,174,200],"context":[3],"of":[4,10,19,35,51,56,58,81,103,145,159,173,178,202,205,215],"network":[5,191],"data,":[6],"bipartite":[7,60,190],"networks":[8],"are":[9,71,90],"particular":[11],"interest,":[12],"as":[13,62,119],"they":[14],"provide":[15],"a":[16,48,59,78,98,115,156,189],"useful":[17],"description":[18],"systems":[20],"representing":[21],"relationships":[22],"between":[23,109],"sending":[24,69],"and":[25,100,180],"receiving":[26,88,110],"nodes.":[27],"this":[29],"framework,":[30],"we":[31,135],"extend":[32],"mixture":[34,80],"latent":[36,82,117,133],"trait":[37,83],"analyzers":[38],"(MLTA)":[39],"model":[40,149,175,185],"with":[41,199,211],"concomitant":[42],"variables":[43],"(nodal":[44],"attributes)":[45],"to":[46,169,188,213],"perform":[47],"joint":[49],"clustering":[50,179],"two":[53],"disjoint":[54],"sets":[55],"nodes":[57,70,89,111],"network,":[61],"in":[63,120,176],"biclustering":[65],"framework.":[66],"detail,":[68],"partitioned":[72,91],"into":[73,92,130,138],"clusters":[74,93],"(called":[75,94],"components)":[76],"via":[77,114],"finite":[79],"models.":[84],"each":[86],"component,":[87],"segments)":[95],"by":[96,126,197],"adopting":[97],"flexible":[99],"parsimonious":[101],"specification":[102],"linear":[105],"predictor.":[106],"Residual":[107],"dependence":[108],"is":[112,162,167,186],"modeled":[113],"multidimensional":[116],"trait,":[118],"original":[122],"MLTA":[123],"specification.":[124],"Furthermore,":[125],"incorporating":[127],"nodal":[128],"attributes":[129,141],"model\u2019s":[132],"layer,":[134],"gain":[136],"insight":[137],"how":[139],"these":[140],"impact":[142],"formation":[144],"components.":[146],"To":[147],"estimate":[148],"parameters,":[150],"an":[151],"EM-type":[152],"algorithm":[153],"based":[154],"on":[155,192],"Gauss-Hermite":[157],"approximation":[158],"intractable":[160],"integrals":[161],"proposed.":[163],"A":[164],"simulation":[165],"study":[166],"conducted":[168],"test":[170],"performance":[172],"terms":[177],"parameters\u2019":[181],"recovery.":[182],"The":[183],"proposed":[184],"applied":[187],"pediatric":[193],"patients":[194,206],"possibly":[195],"affected":[196],"appendicitis":[198],"objective":[201],"identifying":[203],"groups":[204],"(sending":[207],"nodes)":[208],"being":[209],"similar":[210],"respect":[212],"subsets":[214],"clinical":[216],"conditions":[217],"(receiving":[218],"nodes).":[219]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}
