{"id":"https://openalex.org/W2965423010","doi":"https://doi.org/10.1007/s10115-019-01388-5","title":"Dataset-Transformation: improving clustering by enhancing the structure with DipScaling and DipTransformation","display_name":"Dataset-Transformation: improving clustering by enhancing the structure with DipScaling and DipTransformation","publication_year":2019,"publication_date":"2019-08-02","ids":{"openalex":"https://openalex.org/W2965423010","doi":"https://doi.org/10.1007/s10115-019-01388-5","mag":"2965423010"},"language":"en","primary_location":{"id":"doi:10.1007/s10115-019-01388-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10115-019-01388-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10115-019-01388-5.pdf","source":{"id":"https://openalex.org/S81770430","display_name":"Knowledge and Information Systems","issn_l":"0219-1377","issn":["0219-1377","0219-3116"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge and Information Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10115-019-01388-5.pdf","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":true,"raw_author_name":"Benjamin Schelling","raw_affiliation_strings":["Faculty of Computer Science, Research Group Data Mining, University of Vienna, Vienna, Austria"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science, Research Group Data Mining, 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":"Claudia Plant","raw_affiliation_strings":["Faculty of Computer Science, Research Group Data Mining, University of Vienna, Vienna, Austria","ds:UniVie, Vienna, Austria"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science, Research Group Data Mining, University of Vienna, Vienna, Austria","institution_ids":["https://openalex.org/I129774422"]},{"raw_affiliation_string":"ds:UniVie, Vienna, Austria","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5020993896"],"corresponding_institution_ids":["https://openalex.org/I129774422"],"apc_list":{"value":2290,"currency":"EUR","value_usd":2890},"apc_paid":{"value":2290,"currency":"EUR","value_usd":2890},"fwci":0.7225,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.78597441,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"62","issue":"2","first_page":"457","last_page":"484"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9998000264167786,"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":0.9998000264167786,"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/T11106","display_name":"Data Management and Algorithms","score":0.996999979019165,"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"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9958000183105469,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.9043676853179932},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6515421867370605},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6051340699195862},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.5470737218856812},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5432776212692261},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5092135667800903},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.4895878732204437},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.45005157589912415},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.4450902044773102},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.4384108781814575},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.43814557790756226},{"id":"https://openalex.org/keywords/constrained-clustering","display_name":"Constrained clustering","score":0.43428438901901245},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4316871464252472},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.4126776158809662},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.412044882774353},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33772316575050354},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26711273193359375}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.9043676853179932},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6515421867370605},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6051340699195862},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.5470737218856812},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5432776212692261},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5092135667800903},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.4895878732204437},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.45005157589912415},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.4450902044773102},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.4384108781814575},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.43814557790756226},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.43428438901901245},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4316871464252472},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.4126776158809662},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.412044882774353},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33772316575050354},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26711273193359375},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s10115-019-01388-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10115-019-01388-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10115-019-01388-5.pdf","source":{"id":"https://openalex.org/S81770430","display_name":"Knowledge and Information Systems","issn_l":"0219-1377","issn":["0219-1377","0219-3116"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge and Information Systems","raw_type":"journal-article"},{"id":"pmh:info:fedora/oai:univie.ac.at:o:1073126","is_oa":true,"landing_page_url":"https://phaidra.univie.ac.at/o:1073126","pdf_url":null,"source":{"id":"https://openalex.org/S4306401993","display_name":"Phaidra (Universit\u00e4t Wien)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I129774422","host_organization_name":"University of Vienna","host_organization_lineage":["https://openalex.org/I129774422"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISSN:0219-1377","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s10115-019-01388-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10115-019-01388-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10115-019-01388-5.pdf","source":{"id":"https://openalex.org/S81770430","display_name":"Knowledge and Information Systems","issn_l":"0219-1377","issn":["0219-1377","0219-3116"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge and Information Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321691","display_name":"Universit\u00e4t Wien","ror":"https://ror.org/03prydq77"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2965423010.pdf","grobid_xml":"https://content.openalex.org/works/W2965423010.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W1585610988","https://openalex.org/W1673310716","https://openalex.org/W1968881027","https://openalex.org/W1977496278","https://openalex.org/W1997817740","https://openalex.org/W2049633694","https://openalex.org/W2065811242","https://openalex.org/W2070270996","https://openalex.org/W2073459066","https://openalex.org/W2079361215","https://openalex.org/W2102269453","https://openalex.org/W2120636855","https://openalex.org/W2123131881","https://openalex.org/W2162833336","https://openalex.org/W2165874743","https://openalex.org/W2187089797","https://openalex.org/W2353261545","https://openalex.org/W2382141519","https://openalex.org/W2395916081","https://openalex.org/W2533545350","https://openalex.org/W2562836854","https://openalex.org/W2743644771","https://openalex.org/W2809280577","https://openalex.org/W2816855306","https://openalex.org/W2964074409","https://openalex.org/W2999905431","https://openalex.org/W3120740533","https://openalex.org/W4230653117","https://openalex.org/W4254311734"],"related_works":["https://openalex.org/W2181939267","https://openalex.org/W2892323093","https://openalex.org/W2163563073","https://openalex.org/W2970954390","https://openalex.org/W2566341957","https://openalex.org/W2421872988","https://openalex.org/W2162352926","https://openalex.org/W1491908038","https://openalex.org/W2149742493","https://openalex.org/W2810225104"],"abstract_inverted_index":{"A":[0],"data":[1,44,102],"set":[2,45],"might":[3],"have":[4,95],"a":[5,82],"well-defined":[6],"structure,":[7],"but":[8,117],"this":[9,34],"does":[10],"not":[11,108],"necessarily":[12],"lead":[13],"to":[14,37,73,80],"good":[15],"clustering":[16,27,65,107,122],"results.":[17],"If":[18,59],"the":[19,43,60],"structure":[20,61],"is":[21,36,62,113],"hidden":[22],"in":[23],"an":[24],"unfavourable":[25],"scaling,":[26],"will":[28,67],"usually":[29],"fail.":[30],"The":[31],"aim":[32],"of":[33],"work":[35,92],"present":[38],"techniques\u2014DipScaling":[39],"and":[40,48,52,55,78],"DipTransformation\u2014which":[41],"enhance":[42],"by":[46],"rescaling":[47],"transforming":[49],"its":[50,57],"features":[51],"thus":[53],"emphasizing":[54],"accentuating":[56],"structure.":[58],"sufficiently":[63],"clear,":[64],"algorithms":[66,91],"perform":[68],"far":[69],"better.":[70],"We":[71],"refer":[72],"such":[74],"techniques":[75],"as":[76],"\u201cDataset-Transformations\u201d":[77],"try":[79],"provide":[81],"mathematical":[83],"framework":[84],"for":[85,110,119],"them.":[86],"To":[87],"show":[88],"that":[89],"our":[90,114],"well,":[93],"we":[94,105],"conducted":[96],"extensive":[97],"experiments":[98],"on":[99],"several":[100],"real-world":[101],"sets,":[103],"where":[104],"improve":[106],"only":[109],"k-means,":[111],"which":[112],"main":[115],"focus":[116],"also":[118],"other":[120],"standard":[121],"approaches.":[123]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}