{"id":"https://openalex.org/W2907099408","doi":"https://doi.org/10.18420/inf2019_31","title":"Text/Conference Paper","display_name":"Text/Conference Paper","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2907099408","doi":"https://doi.org/10.18420/inf2019_31","mag":"2907099408"},"language":"en","primary_location":{"id":"doi:10.18420/inf2019_31","is_oa":true,"landing_page_url":"https://doi.org/10.18420/inf2019_31","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.18420/inf2019_31","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020993896","display_name":"Benjamin Schelling","orcid":"https://orcid.org/0000-0003-1298-6535"},"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":"Schelling, Benjamin","raw_affiliation_strings":["University of Vienna, Vienna, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Vienna, Vienna, Austria","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":"Plant, Claudia","raw_affiliation_strings":["University of Vienna, Vienna, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Vienna, Vienna, Austria","institution_ids":["https://openalex.org/I129774422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I129774422"],"apc_list":null,"apc_paid":null,"fwci":0.7979,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.79114119,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"407","last_page":"416"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9973000288009644,"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/T11106","display_name":"Data Management and Algorithms","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9216557145118713},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7221148014068604},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.6900591850280762},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6396577954292297},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.6191454529762268},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.5856728553771973},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.5463542938232422},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.5323451161384583},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.5258058905601501},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5226133465766907},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5163372755050659},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4706399142742157},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.4608859717845917},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.4583124816417694},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3670772910118103},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18751582503318787}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.9216557145118713},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7221148014068604},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.6900591850280762},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6396577954292297},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.6191454529762268},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.5856728553771973},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.5463542938232422},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.5323451161384583},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.5258058905601501},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5226133465766907},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5163372755050659},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4706399142742157},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.4608859717845917},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.4583124816417694},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3670772910118103},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18751582503318787},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18420/inf2019_31","is_oa":true,"landing_page_url":"https://doi.org/10.18420/inf2019_31","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"},{"id":"mag:2907099408","is_oa":false,"landing_page_url":"http://dl.gi.de/handle/20.500.12116/24979","pdf_url":null,"source":{"id":"https://openalex.org/S4306419325","display_name":"International Conference on Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"International Conference on Data Mining","raw_type":null}],"best_oa_location":{"id":"doi:10.18420/inf2019_31","is_oa":true,"landing_page_url":"https://doi.org/10.18420/inf2019_31","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1585610988","https://openalex.org/W1968881027","https://openalex.org/W1997817740","https://openalex.org/W2049633694","https://openalex.org/W2079361215","https://openalex.org/W2120636855","https://openalex.org/W2127218421","https://openalex.org/W2145721327","https://openalex.org/W2162833336","https://openalex.org/W2165874743","https://openalex.org/W2220414802","https://openalex.org/W2395916081","https://openalex.org/W2533545350","https://openalex.org/W2743644771","https://openalex.org/W2973651390"],"related_works":["https://openalex.org/W2990320651","https://openalex.org/W143945936","https://openalex.org/W2099058255","https://openalex.org/W2921025746","https://openalex.org/W793359613","https://openalex.org/W1003495524","https://openalex.org/W2429239492","https://openalex.org/W2940914226","https://openalex.org/W2612804315","https://openalex.org/W2188182443","https://openalex.org/W2299970041","https://openalex.org/W2981792919","https://openalex.org/W2789495588","https://openalex.org/W2503159166","https://openalex.org/W2353261545","https://openalex.org/W1997817740","https://openalex.org/W2998383808","https://openalex.org/W3180982373","https://openalex.org/W1568109190","https://openalex.org/W20281709"],"abstract_inverted_index":{"A":[0],"data":[1,44,86],"set":[2,45],"might":[3],"have":[4,79],"a":[5,39],"well-defined":[6],"structure,":[7],"but":[8,101],"this":[9,34],"does":[10],"not":[11,92],"necessarily":[12],"lead":[13],"to":[14,37],"good":[15],"clustering":[16,27,65,91,106],"results.":[17],"If":[18,59],"the":[19,43,60],"structure":[20,61],"is":[21,36,62,97],"hidden":[22],"in":[23],"an":[24],"unfavourable":[25],"scaling,":[26],"will":[28,67],"usually":[29],"fail.":[30],"The":[31],"aim":[32],"of":[33],"work":[35],"present":[38],"technique":[40],"which":[41,96],"enhances":[42],"by":[46],"re-scaling":[47],"and":[48,52,55],"transforming":[49],"its":[50,57],"features":[51],"thus":[53],"emphasizing":[54],"accentuating":[56],"structure.":[58],"sufficiently":[63],"clear,":[64],"algorithms":[66],"perform":[68],"far":[69],"better.":[70],"To":[71],"show":[72],"that":[73],"our":[74,98],"algorithm":[75],"works":[76],"well,":[77],"we":[78,89],"conducted":[80],"extensive":[81],"experiments":[82],"on":[83],"several":[84],"real-world":[85],"sets,":[87],"where":[88],"improve":[90],"only":[93],"for":[94,103],"k-means,":[95],"main":[99],"focus,":[100],"also":[102],"other":[104],"standard":[105],"algorithms.":[107]},"counts_by_year":[{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
