{"id":"https://openalex.org/W4415428238","doi":"https://doi.org/10.3233/faia251192","title":"Parameter Selection for DBSCAN: Insights from Persistent Homology","display_name":"Parameter Selection for DBSCAN: Insights from Persistent Homology","publication_year":2025,"publication_date":"2025-10-21","ids":{"openalex":"https://openalex.org/W4415428238","doi":"https://doi.org/10.3233/faia251192"},"language":null,"primary_location":{"id":"doi:10.3233/faia251192","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia251192","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.3233/faia251192","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070112977","display_name":"Anna Beer","orcid":"https://orcid.org/0000-0002-6890-997X"},"institutions":[{"id":"https://openalex.org/I129774422","display_name":"University of Vienna","ror":"https://ror.org/03prydq77","country_code":"AT","type":"education","lineage":["https://openalex.org/I129774422"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Anna Beer","raw_affiliation_strings":["University of Vienna, Faculty of Computer Science"],"affiliations":[{"raw_affiliation_string":"University of Vienna, Faculty of Computer Science","institution_ids":["https://openalex.org/I129774422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107871799","display_name":"Ekaterina Kuznetsova","orcid":null},"institutions":[{"id":"https://openalex.org/I129774422","display_name":"University of Vienna","ror":"https://ror.org/03prydq77","country_code":"AT","type":"education","lineage":["https://openalex.org/I129774422"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Ekaterina Kuznetsova","raw_affiliation_strings":["University of Vienna, Faculty of Computer Science"],"affiliations":[{"raw_affiliation_string":"University of Vienna, Faculty of Computer Science","institution_ids":["https://openalex.org/I129774422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009516958","display_name":"Claudia Plant","orcid":"https://orcid.org/0000-0001-5274-8123"},"institutions":[{"id":"https://openalex.org/I129774422","display_name":"University of Vienna","ror":"https://ror.org/03prydq77","country_code":"AT","type":"education","lineage":["https://openalex.org/I129774422"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Claudia Plant","raw_affiliation_strings":["University of Vienna, Faculty of Computer Science"],"affiliations":[{"raw_affiliation_string":"University of Vienna, Faculty of Computer Science","institution_ids":["https://openalex.org/I129774422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5070112977"],"corresponding_institution_ids":["https://openalex.org/I129774422"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68166311,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9408000111579895,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9408000111579895,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/persistent-homology","display_name":"Persistent homology","score":0.8817999958992004},{"id":"https://openalex.org/keywords/topological-data-analysis","display_name":"Topological data analysis","score":0.8428999781608582},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7983999848365784},{"id":"https://openalex.org/keywords/dbscan","display_name":"DBSCAN","score":0.59170001745224},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.46639999747276306},{"id":"https://openalex.org/keywords/homology","display_name":"Homology (biology)","score":0.4214000105857849},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.33640000224113464},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.33160001039505005}],"concepts":[{"id":"https://openalex.org/C2874115","wikidata":"https://www.wikidata.org/wiki/Q17099562","display_name":"Persistent homology","level":2,"score":0.8817999958992004},{"id":"https://openalex.org/C2776477805","wikidata":"https://www.wikidata.org/wiki/Q4460773","display_name":"Topological data analysis","level":2,"score":0.8428999781608582},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7983999848365784},{"id":"https://openalex.org/C46576248","wikidata":"https://www.wikidata.org/wiki/Q1114630","display_name":"DBSCAN","level":5,"score":0.59170001745224},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5799000263214111},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.51419997215271},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.46639999747276306},{"id":"https://openalex.org/C165525559","wikidata":"https://www.wikidata.org/wiki/Q224180","display_name":"Homology (biology)","level":3,"score":0.4214000105857849},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3278999924659729},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.31470000743865967},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.31290000677108765},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3095000088214874},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.2906000018119812},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2802000045776367},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2777999937534332},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27459999918937683},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.2572999894618988},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.25220000743865967},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25119999051094055},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.25}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia251192","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia251192","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia251192","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia251192","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Density-based":[0],"clustering":[1,42,72,148],"algorithms":[2,129],"like":[3],"DBSCAN":[4,126],"are":[5],"highly":[6],"effective":[7],"but":[8],"sensitive":[9],"to":[10,25,87,106,115,130,150,158],"parameter":[11,38,109,117],"selection,":[12],"particularly":[13],"the":[14,19,34,37,41,45,78,85],"neighborhood":[15],"radius":[16],"(\u03b5)":[17],"and":[18,32,65,74,111,127],"minimum":[20],"number":[21],"of":[22,36,47,91,137],"neighboring":[23],"points":[24],"form":[26],"a":[27,50,81,134,152],"cluster":[28],"(minPts).":[29],"We":[30,76],"analyze":[31],"investigate":[33],"influence":[35],"settings":[39],"onto":[40],"outcome":[43],"under":[44],"lense":[46],"persistent":[48,102],"homology,":[49],"technique":[51,124],"from":[52,101],"topological":[53,59,145],"data":[54,160],"analysis.":[55,161],"Persistent":[56],"homology":[57,103],"analyzes":[58],"features,":[60],"such":[61],"as":[62],"connected":[63],"components":[64],"loops,":[66],"across":[67],"multiple":[68],"spatial":[69],"scales,":[70],"improving":[71],"accuracy":[73],"robustness.":[75],"use":[77],"density-connectivity":[79],"distance,":[80],"recent":[82],"finding":[83],"in":[84],"field,":[86],"allow":[88],"full":[89],"automatization":[90],"our":[92],"approach.":[93],"In":[94],"extensive":[95],"experiments,":[96],"we":[97],"demonstrate":[98],"how":[99],"insights":[100,146],"can":[104],"help":[105],"identify":[107],"optimal":[108],"values":[110],"introduce":[112],"an":[113],"approach":[114],"automate":[116],"selection":[118],"for":[119,154],"density-based":[120],"clustering.":[121],"The":[122],"proposed":[123],"allows":[125],"related":[128],"perform":[131],"effectively":[132],"on":[133],"large":[135],"variety":[136],"datasets":[138],"without":[139],"any":[140],"user":[141],"input.":[142],"It":[143],"combines":[144],"with":[147],"techniques":[149],"provide":[151],"foundation":[153],"robust,":[155],"automated":[156],"approaches":[157],"complex":[159]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-24T00:00:00"}
