{"id":"https://openalex.org/W2554325299","doi":"https://doi.org/10.1109/mlsp.2016.7738888","title":"Combining clusterings with different detail levels","display_name":"Combining clusterings with different detail levels","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2554325299","doi":"https://doi.org/10.1109/mlsp.2016.7738888","mag":"2554325299"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2016.7738888","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2016.7738888","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)","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/A5046854339","display_name":"Oded Kaminsky","orcid":null},"institutions":[{"id":"https://openalex.org/I13955877","display_name":"Bar-Ilan University","ror":"https://ror.org/03kgsv495","country_code":"IL","type":"education","lineage":["https://openalex.org/I13955877"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Oded Kaminsky","raw_affiliation_strings":["Engineering Faculty, Bar-Ilan University, Israel"],"affiliations":[{"raw_affiliation_string":"Engineering Faculty, Bar-Ilan University, Israel","institution_ids":["https://openalex.org/I13955877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005409420","display_name":"Jacob Goldberger","orcid":"https://orcid.org/0000-0002-2225-1914"},"institutions":[{"id":"https://openalex.org/I13955877","display_name":"Bar-Ilan University","ror":"https://ror.org/03kgsv495","country_code":"IL","type":"education","lineage":["https://openalex.org/I13955877"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Jacob Goldberger","raw_affiliation_strings":["Engineering Faculty, Bar-Ilan University, Israel"],"affiliations":[{"raw_affiliation_string":"Engineering Faculty, Bar-Ilan University, Israel","institution_ids":["https://openalex.org/I13955877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5046854339"],"corresponding_institution_ids":["https://openalex.org/I13955877"],"apc_list":null,"apc_paid":null,"fwci":0.167,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5855304,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/cluster-analysis","display_name":"Cluster analysis","score":0.8583865761756897},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6968578100204468},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5698622465133667},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5588318705558777},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5347553491592407},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.50514155626297},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.5051208138465881},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47753655910491943},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4469505846500397},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4465135633945465},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4304489493370056},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.42484280467033386},{"id":"https://openalex.org/keywords/linear-programming","display_name":"Linear programming","score":0.42432790994644165},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1861674189567566},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15285617113113403}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8583865761756897},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6968578100204468},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5698622465133667},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5588318705558777},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5347553491592407},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.50514155626297},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.5051208138465881},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47753655910491943},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4469505846500397},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4465135633945465},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4304489493370056},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.42484280467033386},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.42432790994644165},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1861674189567566},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15285617113113403},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp.2016.7738888","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2016.7738888","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)","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":24,"referenced_works":["https://openalex.org/W1207903865","https://openalex.org/W1576235636","https://openalex.org/W2009685382","https://openalex.org/W2010135967","https://openalex.org/W2069808690","https://openalex.org/W2080795979","https://openalex.org/W2100824854","https://openalex.org/W2110158442","https://openalex.org/W2112301665","https://openalex.org/W2119823327","https://openalex.org/W2121189958","https://openalex.org/W2137935418","https://openalex.org/W2141729166","https://openalex.org/W2142518823","https://openalex.org/W2144660879","https://openalex.org/W2148347694","https://openalex.org/W2149273804","https://openalex.org/W2150742617","https://openalex.org/W2156999391","https://openalex.org/W2168553594","https://openalex.org/W2914959486","https://openalex.org/W6680957539","https://openalex.org/W6681400661","https://openalex.org/W6682171051"],"related_works":["https://openalex.org/W1999117613","https://openalex.org/W2040929534","https://openalex.org/W3022637481","https://openalex.org/W2393816671","https://openalex.org/W3120229345","https://openalex.org/W2804957450","https://openalex.org/W3144143113","https://openalex.org/W2111119584","https://openalex.org/W3039964395","https://openalex.org/W1887359504"],"abstract_inverted_index":{"In":[0],"this":[1],"study":[2],"we":[3,87],"address":[4],"the":[5,33,42,46,57,61,66,81,96,105,109,125,132,136,142,152],"problem":[6,67],"of":[7,11,60,71,111,141],"recovering":[8],"a":[9,12,49,85],"clustering":[10,51,73],"dataset":[13],"based":[14],"on":[15,26,135,147],"several":[16,113],"clusterings":[17,25],"provided":[18,44],"by":[19,45,122],"different":[20,27],"experts.":[21],"These":[22],"experts":[23,47],"provide":[24],"levels":[28],"(coarser":[29],"or":[30],"finer":[31],"than":[32],"others).":[34],"We":[35,64,103],"present":[36],"an":[37,69],"automatic":[38],"algorithm":[39,107,134,144],"that":[40,52],"combines":[41],"information":[43],"into":[48,127],"single":[50],"can":[53],"be":[54],"viewed":[55],"as":[56,68],"average":[58,82,117],"point":[59],"input":[62],"clusterings.":[63],"formulate":[65],"instance":[70],"correlation":[72],"and":[74,95,129],"apply":[75,104],"integer":[76],"linear":[77],"programming":[78],"to":[79,108],"obtain":[80,89],"clustering.":[83,102],"As":[84],"byproduct,":[86],"also":[88],"for":[90],"each":[91],"expert":[92],"its":[93,101],"reliability":[94],"detail":[97],"level":[98],"encoded":[99],"in":[100],"proposed":[106,133,143],"task":[110],"averaging":[112],"image":[114,126],"segmentations.":[115],"The":[116,139],"segmentation":[118,154],"is":[119,145],"efficiently":[120],"computed":[121],"first":[123],"grouping":[124],"superpixels":[128],"then":[130],"applying":[131],"superpixel":[137],"map.":[138],"performance":[140],"demonstrated":[146],"manually":[148],"annotated":[149],"images":[150],"from":[151],"Berkeley":[153],"dataset.":[155]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
