{"id":"https://openalex.org/W4255602232","doi":"https://doi.org/10.3233/ida-140655","title":"Editorial","display_name":"Editorial","publication_year":2014,"publication_date":"2014-06-27","ids":{"openalex":"https://openalex.org/W4255602232","doi":"https://doi.org/10.3233/ida-140655"},"language":"es","primary_location":{"id":"doi:10.3233/ida-140655","is_oa":true,"landing_page_url":"https://doi.org/10.3233/ida-140655","pdf_url":"https://content.iospress.com:443/download/intelligent-data-analysis/ida00655?id=intelligent-data-analysis%2Fida00655","source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-article"},"type":"editorial","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://content.iospress.com:443/download/intelligent-data-analysis/ida00655?id=intelligent-data-analysis%2Fida00655","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086586369","display_name":"A. Famili","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"A. Famili","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5086586369"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.36706131,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"4","first_page":"529","last_page":"530"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.03739999979734421,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.03739999979734421,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.03189999982714653,"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/T13234","display_name":"advanced mathematical theories","score":0.026799999177455902,"subfield":{"id":"https://openalex.org/subfields/2610","display_name":"Mathematical Physics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3043491244316101}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3043491244316101}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ida-140655","is_oa":true,"landing_page_url":"https://doi.org/10.3233/ida-140655","pdf_url":"https://content.iospress.com:443/download/intelligent-data-analysis/ida00655?id=intelligent-data-analysis%2Fida00655","source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3233/ida-140655","is_oa":true,"landing_page_url":"https://doi.org/10.3233/ida-140655","pdf_url":"https://content.iospress.com:443/download/intelligent-data-analysis/ida00655?id=intelligent-data-analysis%2Fida00655","source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4255602232.pdf","grobid_xml":"https://content.openalex.org/works/W4255602232.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2350741829","https://openalex.org/W2130043461","https://openalex.org/W2530322880"],"abstract_inverted_index":{"This":[0],"issue":[1,33,48,117,334,461],"of":[2,7,24,31,59,70,73,79,105,115,131,154,200,246,259,289,332,338,371,459,479,484,521],"the":[3,16,22,40,45,56,60,71,77,80,103,106,112,164,178,188,205,217,222,233,243,260,295,329,336,372,401,406,414,418,430,489,510,525,530],"IDA":[4],"journal":[5],"consists":[6],"eleven":[8],"articles,":[9],"all":[10,184],"covering":[11],"various":[12],"topics":[13],"related":[14],"to":[15,54,127,145,204,273,404,412,454,506,528],"theoretical":[17],"and":[18,37,49,94,122,196,240,255,280,291,313,323,341,380,388,470,497],"applied":[19],"research":[20],"in":[21,86,111,163,242,294,300,328,351,410,423,448,471,488,509,519],"field":[23],"Intelligent":[25],"Data":[26],"Analysis.The":[27],"first":[28,41],"4":[29],"articles":[30,318],"this":[32,87,116,247,301,333,424,449,460,472],"are":[34,263,319,346,365,438,491,517],"about":[35,391],"clustering":[36,121,143,156,253],"unsupervised":[38,238],"learning.In":[39],"article,":[42],"Novoselova":[43],"discusses":[44],"cluster":[46,171,192],"stability":[47],"propose":[50,268],"a":[51,67,129,147,168,198,275,282,441,482,494,498,504],"stability-based":[52],"algorithm":[53,63,272],"estimate":[55],"individual":[57],"clusters":[58,74,190,229],"dendogram.The":[61],"proposed":[62,107,181,399],"is":[64,355,390,403,426,451,464,474,481],"based":[65,186,193,264,271,310,356,366,444],"on":[66,89,98,187,211,250,265,311,320,357,367,377,466,475],"repetitive":[68],"construction":[69],"hierarchy":[72],"followed":[75],"by":[76,386,400,428,462],"calculation":[78],"original":[81],"consensus":[82],"matrix.The":[83],"experiments":[84,298],"reported":[85,299],"article":[88,114,166,245,302,331,374,385,458],"two":[90],"simulated":[91],"data":[92,100,214,277,322,382,485,522],"sets":[93,101,215],"additional":[95],"comparative":[96],"analysis":[97],"real":[99,213,381],"demonstrate":[102,216],"advantages":[104],"approach.Vahidipour":[108],"et":[109,161,326],"al.":[110,162,327],"second":[113],"also":[118,452,465],"discuss":[119,335],"hierarchical":[120,142,155],"consider":[123],"using":[124,191,221],"multiple":[125],"methods":[126,138,437],"generate":[128,274],"set":[130,219],"dendograms.The":[132],"authors":[133,402],"compare":[134,304],"several":[135,212],"weighted":[136],"combination":[137,153],"where":[139,433,486],"they":[140,303],"use":[141,281],"results":[144,149,210,376],"derive":[146],"consensus.Their":[148],"show":[150],"that":[151,226,230,257,345,364,502,516,524],"weighting":[152],"performs":[157],"better":[158,231],"than":[159],"averaging.Hu":[160],"third":[165],"describe":[167,342],"framework":[169,225],"for":[170,207,278,286,348],"improvements":[172],"which":[173],"involves":[174],"user":[175,206],"supervision":[176],"at":[177],"feature":[179,194,218],"level.The":[180],"method":[182],"ranks":[183],"features":[185,203],"recent":[189],"selection":[195],"presents":[197],"list":[199],"highly":[201],"ranked":[202],"labeling.Their":[208],"experimental":[209],"obtained":[220],"new":[223],"interactive":[224],"can":[227],"produce":[228],"match":[232],"user's":[234],"expectations":[235],"compared":[236,439],"with":[237,307,361,440,493],"approach.Ebrahimi":[239],"Abdollahi":[241],"fourth":[244],"group":[248],"focus":[249],"privacy":[251,314],"preserving":[252],"(PPC)":[254],"argue":[256],"most":[258],"existing":[261],"techniques":[262],"heuristic":[266],"notions.They":[267],"an":[269],"-differential":[270],"perturbed":[276],"PPC":[279],"wavelet":[283],"transform":[284],"approach":[285,306,354,446],"reduced":[287],"number":[288],"dimensions":[290],"less":[292],"noise":[293],"data.In":[296],"their":[297,305],"other":[308],"algorithms":[309,344,515],"utility":[312],"guarantees.The":[315],"next":[316,384],"three":[317,514],"temporal":[321,352,359],"frequent":[324,419,434,468],"patterns.Dey":[325],"fifth":[330],"topic":[337],"neighborhood":[339],"discovery":[340,350],"four":[343],"appropriate":[347],"knowledge":[349],"data.Their":[353],"identifying":[358],"neighborhoods":[360],"distinct":[362],"demarcations":[363],"unequal":[368],"depth":[369],"discretization":[370],"data.The":[373],"contains":[375],"both":[378],"synthetic":[379],"sets.The":[383],"Shaw":[387],"Gopalan":[389],"discovering":[392],"meaningful":[393],"trajectories":[394,416],"from":[395,417],"dynamic":[396],"objects.The":[397],"idea":[398],"apply":[405],"association-based":[407],"mining":[408,467],"concepts":[409],"order":[411],"find":[413],"longest":[415],"trajectory":[420],"patterns.The":[421],"path":[422],"case":[425,473],"derived":[427],"applying":[429],"modified":[431],"apriori":[432],"pattern":[435],"tree":[436],"standard":[442],"graph":[443],"methods.The":[445],"given":[447],"paper":[450],"applicable":[453],"game":[455],"theory.The":[456],"seventh":[457],"Liu":[463],"patterns,":[469],"uncertain":[476],"univariate":[477],"class":[478,483],"data.This":[480],"attributes":[487],"transactions":[490],"associated":[492],"quantitative":[495],"interval":[496],"probability":[499,505],"density":[500],"function":[501],"assigns":[503],"each":[507],"value":[508],"interval.The":[511],"author":[512],"proposes":[513],"different":[518],"terms":[520],"format":[523],"structures":[526],"used":[527],"store":[529],"data.":[531]},"counts_by_year":[],"updated_date":"2026-03-03T08:47:05.690250","created_date":"2022-05-12T00:00:00"}