{"id":"https://openalex.org/W2473012037","doi":"https://doi.org/10.1515/jisys-2014-0172","title":"DBSCANI: Noise-Resistant Method for Missing Value Imputation","display_name":"DBSCANI: Noise-Resistant Method for Missing Value Imputation","publication_year":2015,"publication_date":"2015-07-10","ids":{"openalex":"https://openalex.org/W2473012037","doi":"https://doi.org/10.1515/jisys-2014-0172","mag":"2473012037"},"language":"en","primary_location":{"id":"doi:10.1515/jisys-2014-0172","is_oa":true,"landing_page_url":"https://doi.org/10.1515/jisys-2014-0172","pdf_url":null,"source":{"id":"https://openalex.org/S2764846071","display_name":"Journal of Intelligent Systems","issn_l":"0334-1860","issn":["0334-1860","2191-026X"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315148","host_organization_name":"IlmuKomputer.Com","host_organization_lineage":["https://openalex.org/P4310315148"],"host_organization_lineage_names":["IlmuKomputer.Com"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1515/jisys-2014-0172","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073040093","display_name":"Archana Purwar","orcid":"https://orcid.org/0000-0001-8824-4859"},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Archana Purwar","raw_affiliation_strings":["Department of Computer Science and Information Technology, JIIT Noida, India","1Department of Computer Science and Information Technology, JIIT Noida, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Technology, JIIT Noida, India","institution_ids":["https://openalex.org/I154970844"]},{"raw_affiliation_string":"1Department of Computer Science and Information Technology, JIIT Noida, India","institution_ids":["https://openalex.org/I154970844"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032397117","display_name":"Sandeep Kumar Singh","orcid":"https://orcid.org/0000-0002-2781-8684"},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sandeep Kumar Singh","raw_affiliation_strings":["Department of Computer Science and Information Technology, JIIT Noida, India","1Department of Computer Science and Information Technology, JIIT Noida, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Technology, JIIT Noida, India","institution_ids":["https://openalex.org/I154970844"]},{"raw_affiliation_string":"1Department of Computer Science and Information Technology, JIIT Noida, India","institution_ids":["https://openalex.org/I154970844"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5073040093"],"corresponding_institution_ids":["https://openalex.org/I154970844"],"apc_list":{"value":1000,"currency":"EUR","value_usd":1078},"apc_paid":{"value":1000,"currency":"EUR","value_usd":1078},"fwci":0.8904,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.84596675,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"25","issue":"3","first_page":"431","last_page":"440"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9991999864578247,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9991999864578247,"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":0.9965999722480774,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.782289445400238},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.7594585418701172},{"id":"https://openalex.org/keywords/dbscan","display_name":"DBSCAN","score":0.7318277955055237},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.665971040725708},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6324368715286255},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.6106688976287842},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5121071338653564},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5049846768379211},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4901677072048187},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4806193709373474},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43247485160827637},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.4310644268989563},{"id":"https://openalex.org/keywords/k-means-clustering","display_name":"k-means clustering","score":0.42544299364089966},{"id":"https://openalex.org/keywords/determining-the-number-of-clusters-in-a-data-set","display_name":"Determining the number of clusters in a data set","score":0.42012789845466614},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.30368924140930176},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2802511155605316},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.23892301321029663},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23120170831680298},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.21996766328811646},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07665589451789856}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.782289445400238},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.7594585418701172},{"id":"https://openalex.org/C46576248","wikidata":"https://www.wikidata.org/wiki/Q1114630","display_name":"DBSCAN","level":5,"score":0.7318277955055237},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.665971040725708},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6324368715286255},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.6106688976287842},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5121071338653564},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5049846768379211},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4901677072048187},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4806193709373474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43247485160827637},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.4310644268989563},{"id":"https://openalex.org/C207968372","wikidata":"https://www.wikidata.org/wiki/Q310401","display_name":"k-means clustering","level":3,"score":0.42544299364089966},{"id":"https://openalex.org/C149872217","wikidata":"https://www.wikidata.org/wiki/Q5265701","display_name":"Determining the number of clusters in a data set","level":5,"score":0.42012789845466614},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.30368924140930176},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2802511155605316},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.23892301321029663},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23120170831680298},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.21996766328811646},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07665589451789856},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1515/jisys-2014-0172","is_oa":true,"landing_page_url":"https://doi.org/10.1515/jisys-2014-0172","pdf_url":null,"source":{"id":"https://openalex.org/S2764846071","display_name":"Journal of Intelligent Systems","issn_l":"0334-1860","issn":["0334-1860","2191-026X"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315148","host_organization_name":"IlmuKomputer.Com","host_organization_lineage":["https://openalex.org/P4310315148"],"host_organization_lineage_names":["IlmuKomputer.Com"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:bbed0e448c4d44fc8f61524484f011d5","is_oa":true,"landing_page_url":"https://doaj.org/article/bbed0e448c4d44fc8f61524484f011d5","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Intelligent Systems, Vol 25, Iss 3, Pp 431-440 (2016)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1515/jisys-2014-0172","is_oa":true,"landing_page_url":"https://doi.org/10.1515/jisys-2014-0172","pdf_url":null,"source":{"id":"https://openalex.org/S2764846071","display_name":"Journal of Intelligent Systems","issn_l":"0334-1860","issn":["0334-1860","2191-026X"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310315148","host_organization_name":"IlmuKomputer.Com","host_organization_lineage":["https://openalex.org/P4310315148"],"host_organization_lineage_names":["IlmuKomputer.Com"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/12","display_name":"Responsible consumption and production"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1495018677","https://openalex.org/W1565377632","https://openalex.org/W1888898201","https://openalex.org/W1988176704","https://openalex.org/W1988904801","https://openalex.org/W1995790322","https://openalex.org/W2034841618","https://openalex.org/W2049633694","https://openalex.org/W2062063985","https://openalex.org/W2068022129","https://openalex.org/W2080339024","https://openalex.org/W2101873033","https://openalex.org/W2116516274","https://openalex.org/W2124491466","https://openalex.org/W2127841934","https://openalex.org/W2140190241","https://openalex.org/W2151004739","https://openalex.org/W2162210260","https://openalex.org/W2322164978","https://openalex.org/W3120740533"],"related_works":["https://openalex.org/W2988820721","https://openalex.org/W2281933227","https://openalex.org/W2538524215","https://openalex.org/W4246086898","https://openalex.org/W3208106817","https://openalex.org/W2384509060","https://openalex.org/W2152604726","https://openalex.org/W63947076","https://openalex.org/W2976609042","https://openalex.org/W2295884465"],"abstract_inverted_index":{"Abstract":[0],"The":[1,13,27,131,176],"quality":[2,28],"of":[3,15,24,29,36,73,82,112,153,178],"data":[4,11,21,30,47,129,149,161,170,174,213],"is":[5,18,22,182,194,206],"an":[6],"important":[7],"task":[8],"in":[9,34,45,55,66,109,127,147],"the":[10,46,71,110,121,139,144,148,159,179],"mining.":[12],"validity":[14],"mining":[16],"algorithms":[17],"reduced":[19],"if":[20],"not":[23],"good":[25],"quality.":[26],"can":[31],"be":[32],"assessed":[33],"terms":[35],"missing":[37],"values":[38,108],"(MV)":[39],"as":[40,42,136,190,192],"well":[41,191],"noise":[43,65,85,145,208],"present":[44],"set.":[48,150],"Various":[49],"imputation":[50,98,199],"techniques":[51],"have":[52,155],"been":[53,62,156],"studied":[54],"MV":[56,89],"study,":[57],"but":[58],"little":[59],"attention":[60],"has":[61,77],"given":[63],"on":[64,101,158,212],"earlier":[67],"work.":[68],"Moreover,":[69],"to":[70,104,124,143],"best":[72],"knowledge,":[74],"no":[75],"one":[76],"used":[78,215],"density-based":[79,97,102],"spatial":[80,128],"clustering":[81,87,103,115],"applications":[83],"with":[84,106,196],"(DBSCAN)":[86],"for":[88],"imputation.":[90],"This":[91],"paper":[92],"proposes":[93],"a":[94],"novel":[95],"technique":[96],"(DBSCANI)":[99],"built":[100],"deal":[105],"incomplete":[107],"presence":[111],"noise.":[113],"Density-based":[114],"algorithm":[116],"proposed":[117,180],"by":[118],"Kriegal":[119],"groups":[120],"objects":[122,146],"according":[123],"their":[125],"density":[126],"bases.":[130],"high-density":[132],"regions":[133,141],"are":[134],"known":[135],"clusters,":[137],"and":[138,167],"low-density":[140],"refer":[142],"A":[151],"lot":[152],"experiments":[154],"performed":[157],"Iris":[160],"set":[162,171],"from":[163,172],"life":[164],"science":[165],"domain":[166],"Jain\u2019s":[168],"(2D)":[169],"shape":[173],"sets.":[175],"performance":[177],"method":[181,205],"evaluated":[183],"using":[184],"root":[185],"mean":[186],"square":[187],"error":[188],"(RMSE)":[189],"it":[193],"compared":[195],"existing":[197],"K-means":[198],"(KMI).":[200],"Results":[201],"show":[202],"that":[203],"our":[204],"more":[207],"resistant":[209],"than":[210],"KMI":[211],"sets":[214],"under":[216],"study.":[217]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2},{"year":2017,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
