{"id":"https://openalex.org/W3022649143","doi":"https://doi.org/10.1080/03610918.2020.1759637","title":"The generalized Pitman measure of similarity and hierarchical clustering","display_name":"The generalized Pitman measure of similarity and hierarchical clustering","publication_year":2020,"publication_date":"2020-05-06","ids":{"openalex":"https://openalex.org/W3022649143","doi":"https://doi.org/10.1080/03610918.2020.1759637","mag":"3022649143"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2020.1759637","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2020.1759637","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","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/A5007208571","display_name":"Arman Reybod","orcid":"https://orcid.org/0000-0001-6150-9319"},"institutions":[{"id":"https://openalex.org/I97626857","display_name":"University of Birjand","ror":"https://ror.org/03g4hym73","country_code":"IR","type":"education","lineage":["https://openalex.org/I97626857"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Arman Reybod","raw_affiliation_strings":["Department of Statistics, School of Mathematical Science and Statistics, University of Birjand, Birjand, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, School of Mathematical Science and Statistics, University of Birjand, Birjand, Iran","institution_ids":["https://openalex.org/I97626857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112350556","display_name":"Javad Etminan","orcid":null},"institutions":[{"id":"https://openalex.org/I97626857","display_name":"University of Birjand","ror":"https://ror.org/03g4hym73","country_code":"IR","type":"education","lineage":["https://openalex.org/I97626857"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Javad Etminan","raw_affiliation_strings":["Department of Statistics, School of Mathematical Science and Statistics, University of Birjand, Birjand, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, School of Mathematical Science and Statistics, University of Birjand, Birjand, Iran","institution_ids":["https://openalex.org/I97626857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081830188","display_name":"Rahim Moineddin","orcid":"https://orcid.org/0000-0002-5506-084X"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]},{"id":"https://openalex.org/I4210125326","display_name":"Public Health Ontario","ror":"https://ror.org/025z8ah66","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I4210125326"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Rahim Moineddin","raw_affiliation_strings":["Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada"],"affiliations":[{"raw_affiliation_string":"Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada","institution_ids":["https://openalex.org/I4210125326","https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053045356","display_name":"Adel Mohammadpour","orcid":"https://orcid.org/0000-0002-5079-7025"},"institutions":[{"id":"https://openalex.org/I158248296","display_name":"Amirkabir University of Technology","ror":"https://ror.org/04gzbav43","country_code":"IR","type":"education","lineage":["https://openalex.org/I158248296"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Adel Mohammadpour","raw_affiliation_strings":["Department of Statistics, Amirkabir University of Technology, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Amirkabir University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I158248296"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5007208571"],"corresponding_institution_ids":["https://openalex.org/I97626857"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04509912,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"51","issue":"9","first_page":"5190","last_page":"5201"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9936000108718872,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9936000108718872,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9907000064849854,"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/T10057","display_name":"Face and Expression Recognition","score":0.9345999956130981,"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/measure","display_name":"Measure (data warehouse)","score":0.6703159809112549},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.6481454372406006},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5916882157325745},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.5690686702728271},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5508428812026978},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4488331973552704},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3781760334968567},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35731542110443115},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3387283682823181},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3376954197883606},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3281250298023224}],"concepts":[{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6703159809112549},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.6481454372406006},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5916882157325745},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.5690686702728271},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5508428812026978},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4488331973552704},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3781760334968567},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35731542110443115},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3387283682823181},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3376954197883606},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3281250298023224},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2020.1759637","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2020.1759637","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W602946569","https://openalex.org/W1594924988","https://openalex.org/W1978189606","https://openalex.org/W2001619934","https://openalex.org/W2033403400","https://openalex.org/W2054787086","https://openalex.org/W2149844502","https://openalex.org/W2313094819","https://openalex.org/W2791070031","https://openalex.org/W3105265400","https://openalex.org/W4235169531","https://openalex.org/W4292890447","https://openalex.org/W4298882835"],"related_works":["https://openalex.org/W2358805260","https://openalex.org/W2326113450","https://openalex.org/W1488437289","https://openalex.org/W1538862850","https://openalex.org/W2187249578","https://openalex.org/W2399400609","https://openalex.org/W2331403358","https://openalex.org/W2390573116","https://openalex.org/W2189105355","https://openalex.org/W4237625828"],"abstract_inverted_index":{"Pitman":[0],"measure":[1,29,39],"of":[2,36],"closeness":[3],"(PMC)":[4],"is":[5,14],"a":[6,26],"criterion":[7],"to":[8,16,21],"show":[9],"how":[10],"much":[11],"an":[12],"estimator":[13],"close":[15],"its":[17],"parameter":[18],"with":[19],"respect":[20],"another":[22],"estimator.":[23],"We":[24],"develop":[25],"new":[27],"similarity":[28,38],"which":[30],"uses":[31],"PMC":[32],"on":[33],"the":[34,37],"basis":[35],"for":[40,48],"hierarchical":[41],"clustering":[42],"algorithm":[43],"that":[44],"has":[45],"better":[46],"performance":[47],"heavy-tailed":[49],"data.":[50]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}