{"id":"https://openalex.org/W2613238811","doi":"https://doi.org/10.4018/ijdwm.2017040104","title":"Robust Clustering with Distance and Density","display_name":"Robust Clustering with Distance and Density","publication_year":2017,"publication_date":"2017-04-01","ids":{"openalex":"https://openalex.org/W2613238811","doi":"https://doi.org/10.4018/ijdwm.2017040104","mag":"2613238811"},"language":"en","primary_location":{"id":"doi:10.4018/ijdwm.2017040104","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijdwm.2017040104","pdf_url":null,"source":{"id":"https://openalex.org/S53932126","display_name":"International Journal of Data Warehousing and Mining","issn_l":"1548-3924","issn":["1548-3924","1548-3932"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Warehousing and Mining","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/A5101453272","display_name":"Hanning Yuan","orcid":"https://orcid.org/0000-0003-4313-1038"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanning Yuan","raw_affiliation_strings":["School of Software, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000423121","display_name":"Shuliang Wang","orcid":"https://orcid.org/0000-0001-5326-7209"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuliang Wang","raw_affiliation_strings":["School of Software, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075547106","display_name":"Jing Geng","orcid":"https://orcid.org/0000-0002-2273-9645"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Geng","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111972593","display_name":"Yang Yu","orcid":"https://orcid.org/0000-0002-0784-9715"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Yu","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081645776","display_name":"Ming Zhong","orcid":"https://orcid.org/0000-0002-4022-6800"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Zhong","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.1994,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61142934,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"13","issue":"2","first_page":"63","last_page":"74"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9994000196456909,"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":0.9994000196456909,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9846000075340271,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9804999828338623,"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/dbscan","display_name":"DBSCAN","score":0.9286966323852539},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8830923438072205},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7074086666107178},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.5640522837638855},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.5560879111289978},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5217038989067078},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5182673931121826},{"id":"https://openalex.org/keywords/k-medians-clustering","display_name":"k-medians clustering","score":0.47328469157218933},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.4574398994445801},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.44504356384277344},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4145379662513733},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3867507874965668}],"concepts":[{"id":"https://openalex.org/C46576248","wikidata":"https://www.wikidata.org/wiki/Q1114630","display_name":"DBSCAN","level":5,"score":0.9286966323852539},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8830923438072205},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7074086666107178},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.5640522837638855},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.5560879111289978},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5217038989067078},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5182673931121826},{"id":"https://openalex.org/C115328559","wikidata":"https://www.wikidata.org/wiki/Q4041956","display_name":"k-medians clustering","level":5,"score":0.47328469157218933},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.4574398994445801},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.44504356384277344},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4145379662513733},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3867507874965668},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4018/ijdwm.2017040104","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijdwm.2017040104","pdf_url":null,"source":{"id":"https://openalex.org/S53932126","display_name":"International Journal of Data Warehousing and Mining","issn_l":"1548-3924","issn":["1548-3924","1548-3932"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Warehousing and Mining","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:igg:jdwm00:v:13:y:2017:i:2:p:63-74","is_oa":false,"landing_page_url":"https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJDWM.2017040104","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"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":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W142212369","https://openalex.org/W1673310716","https://openalex.org/W1972098431","https://openalex.org/W1972257410","https://openalex.org/W1972969203","https://openalex.org/W1993586168","https://openalex.org/W2067847824","https://openalex.org/W2089016176","https://openalex.org/W2103560185","https://openalex.org/W2105979014","https://openalex.org/W2125464731","https://openalex.org/W2130623086","https://openalex.org/W2150734399","https://openalex.org/W2159936323","https://openalex.org/W2165232124","https://openalex.org/W2165835468","https://openalex.org/W2273477544","https://openalex.org/W2295256067","https://openalex.org/W2369681739","https://openalex.org/W2375759205","https://openalex.org/W2551844785","https://openalex.org/W4213009331"],"related_works":["https://openalex.org/W2394193399","https://openalex.org/W2054669762","https://openalex.org/W2387373525","https://openalex.org/W2809859387","https://openalex.org/W2353158678","https://openalex.org/W2604015980","https://openalex.org/W2377732725","https://openalex.org/W4292621762","https://openalex.org/W3028306937","https://openalex.org/W4390954627"],"abstract_inverted_index":{"Clustering":[0],"is":[1,11,59,93],"fundamental":[2],"for":[3,95,98],"using":[4],"big":[5,48,63],"data.":[6,49],"However,":[7],"AP":[8,57,83],"(affinity":[9],"propagation)":[10],"not":[12],"good":[13],"at":[14],"non-convex":[15],"datasets,":[16],"and":[17,71,134,144],"the":[18,52,66,82,91,102,112],"input":[19],"parameter":[20,55],"has":[21,125,139],"a":[22,54,76,107],"marked":[23],"impact":[24],"on":[25,65,118],"DBSCAN":[26],"(density-based":[27],"spatial":[28],"clustering":[29,97,104,114,129],"of":[30,68,78],"applications":[31],"with":[32],"noise).":[33],"Moreover,":[34],"new":[35],"characteristics":[36],"such":[37],"as":[38],"volume,":[39],"variety,":[40],"velocity,":[41],"veracity":[42],"make":[43],"it":[44,74,137],"difficult":[45],"to":[46,61,110],"group":[47,62,77],"To":[50],"address":[51],"issues,":[53],"free":[56],"(PFAP)":[58],"proposed":[60],"data":[64],"basis":[67],"both":[69],"distance":[70],"density.":[72],"Firstly,":[73],"obtains":[75],"normalized":[79],"density":[80,92,96],"from":[81],"clustering.":[84],"The":[85],"estimated":[86],"parameters":[87],"are":[88],"monotonically.":[89],"Then,":[90],"used":[94],"multiple":[99],"times.":[100],"Finally,":[101],"multiple-density":[103],"results":[105,117],"undergo":[106],"two-stage":[108],"amalgamation":[109],"achieve":[111],"final":[113],"result.":[115],"Experimental":[116],"several":[119],"benchmark":[120],"datasets":[121],"show":[122],"that":[123],"PFAP":[124],"been":[126],"achieved":[127],"better":[128,140],"quality":[130],"than":[131,142],"DBSCAN,":[132],"AP,":[133],"APSCAN.":[135],"And":[136],"also":[138],"performance":[141],"APSCAN":[143],"FSDP.":[145]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T06:19:23.411458","created_date":"2025-10-10T00:00:00"}