{"id":"https://openalex.org/W7141685387","doi":"https://doi.org/10.55041/isjem05905","title":"Machine Learning Techniques for Cleaning Raw Data","display_name":"Machine Learning Techniques for Cleaning Raw Data","publication_year":2026,"publication_date":"2026-03-27","ids":{"openalex":"https://openalex.org/W7141685387","doi":"https://doi.org/10.55041/isjem05905"},"language":"en","primary_location":{"id":"doi:10.55041/isjem05905","doi":"https://doi.org/10.55041/isjem05905","is_oa":false,"landing_page_url":"https://doi.org/10.55041/isjem05905","pdf_url":null,"source":{"id":"https://openalex.org/S4387287997","display_name":"International Scientific Journal of Engineering and Management","issn_l":"2583-6129","issn":["2583-6129"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Scientific Journal of Engineering &amp; Management","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W7141685387"],"child_works_count":0,"type":"article","is_traditional":true,"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/A5114849366","display_name":"Jaspreet Kaur","orcid":"https://orcid.org/0009-0009-4833-0926","observed_orcids":["https://orcid.org/0009-0009-4833-0926"]},"institutions":[{"id":"https://openalex.org/I4405258633","display_name":"Rungta College of Engineering and Technology","ror":"https://ror.org/010gah044","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405258633","https://openalex.org/I4405259702"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Jaspreet Kaur","raw_affiliation_strings":["Department of Information Technology RCET, Bhilai, Chhattisgarh, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology RCET, Bhilai, Chhattisgarh, India","institution_ids":["https://openalex.org/I4405258633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050195364","display_name":"Neelabh Sao","orcid":"https://orcid.org/0000-0003-4110-6293","observed_orcids":["https://orcid.org/0000-0003-4110-6293"]},"institutions":[{"id":"https://openalex.org/I4405258633","display_name":"Rungta College of Engineering and Technology","ror":"https://ror.org/010gah044","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405258633","https://openalex.org/I4405259702"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Dr. Neelabh Sao","raw_affiliation_strings":["Department of Information Technology RCET, Bhilai, Chhattisgarh, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology RCET, Bhilai, Chhattisgarh, India","institution_ids":["https://openalex.org/I4405258633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4405258633"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"05","issue":"03","first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.8794000148773193,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11719","display_name":"Data Quality and Management","score":0.8794000148773193,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.11879999935626984,"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/data-cleaning","display_name":"data cleaning","score":0.9990000128746033},{"id":"https://openalex.org/keywords/data-quality","display_name":"data quality","score":0.8309999704360962},{"id":"https://openalex.org/keywords/missing-data","display_name":"missing data","score":0.796999990940094},{"id":"https://openalex.org/keywords/imputation","display_name":"imputation","score":0.7680000066757202},{"id":"https://openalex.org/keywords/outlier-detection","display_name":"outlier detection","score":0.968999981880188},{"id":"https://openalex.org/keywords/data-inconsistency","display_name":"data inconsistency","score":0.8500000238418579},{"id":"https://openalex.org/keywords/noisy-data","display_name":"noisy data","score":0.6970000267028809},{"id":"https://openalex.org/keywords/data-preprocessing","display_name":"data preprocessing","score":0.6819999814033508},{"id":"https://openalex.org/keywords/machine-learning-pipelines","display_name":"machine learning pipelines","score":0.7929999828338623},{"id":"https://openalex.org/keywords/data-imperfections","display_name":"data imperfections","score":0.5289999842643738}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7239999771118164},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7170000076293945},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.682200014591217},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6083999872207642},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.48399999737739563},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.45809999108314514},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.44359999895095825},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.4410000145435333},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.435699999332428},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.420199990272522},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.39660000801086426},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.3467999994754791},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3391000032424927},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3325999975204468},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.319599986076355},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C13926793","wikidata":"https://www.wikidata.org/wiki/Q3507155","display_name":"Group method of data handling","level":2,"score":0.2646999955177307},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C115903097","wikidata":"https://www.wikidata.org/wiki/Q7094097","display_name":"Online machine learning","level":3,"score":0.25440001487731934},{"id":"https://openalex.org/C2777655017","wikidata":"https://www.wikidata.org/wiki/Q1501161","display_name":"Toolbox","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.55041/isjem05905","doi":"https://doi.org/10.55041/isjem05905","is_oa":false,"landing_page_url":"https://doi.org/10.55041/isjem05905","pdf_url":null,"source":{"id":"https://openalex.org/S4387287997","display_name":"International Scientific Journal of Engineering and Management","issn_l":"2583-6129","issn":["2583-6129"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Scientific Journal of Engineering &amp; Management","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W6911604718","https://openalex.org/W4399513333","https://openalex.org/W4382810915","https://openalex.org/W4400580273","https://openalex.org/W7134825097","https://openalex.org/W2960422917","https://openalex.org/W2959835336","https://openalex.org/W7170152250","https://openalex.org/W4409892338","https://openalex.org/W4220991771"],"abstract_inverted_index":{"Machine":[0,146],"learning":[1,55,117],"(ML)":[2],"systems":[3],"typically":[4],"rely":[5],"on":[6,45],"high-quality,":[7],"well-structured":[8],"datasets":[9],"for":[10,82,105],"effective":[11],"performance.However,":[12],"data":[13,46,63,91,113,123],"collected":[14],"from":[15],"real-world":[16,98],"environments":[17],"is":[18],"often":[19],"incomplete,":[20],"noisy,":[21],"inconsistent,":[22],"and":[23,32,37,49,66,90,108],"heterogeneous.Such":[24],"imperfections":[25,64],"negatively":[26],"impact":[27],"model":[28],"accuracy,":[29],"generalization":[30],"ability,":[31],"reliability,":[33],"particularly":[34],"in":[35,52,97],"dynamic":[36],"large-scale":[38],"applications.":[39],"This":[40],"study":[41,120],"reviews":[42],"existing":[43],"research":[44],"cleaning":[47,114],"techniques":[48],"their":[50,95],"role":[51],"improving":[53],"machine":[54],"outcomes.":[56],"It":[57],"examines":[58],"how":[59,67],"different":[60],"types":[61],"of":[62,72],"arise":[65],"they":[68],"influence":[69],"various":[70],"stages":[71],"the":[73,103,116,133],"ML":[74,134],"pipeline.":[75],"The":[76,119],"review":[77],"also":[78],"evaluates":[79],"current":[80],"approaches":[81],"handling":[83],"issues":[84],"such":[85],"as":[86,128,138],"missing":[87],"values,":[88],"outliers,":[89],"inconsistencies,":[92],"along":[93],"with":[94],"limitations":[96],"scenarios.":[99],"Furthermore,":[100],"it":[101],"highlights":[102],"need":[104],"more":[106],"adaptive":[107],"scalable":[109],"solutions":[110],"that":[111,122],"integrate":[112],"within":[115],"process.":[118],"concludes":[121],"quality":[124],"should":[125],"be":[126],"treated":[127],"a":[129,139],"critical":[130],"factor":[131],"throughout":[132],"lifecycle":[135],"rather":[136],"than":[137],"standalone":[140],"pre-processing":[141],"step.":[142],"Keywords:":[143],"Data":[144,148],"Cleaning,":[145],"Learning,":[147],"Pre-processing,":[149],"Outlier":[150],"Detection,":[151],"Imputation":[152]},"counts_by_year":[],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2026-03-28T00:00:00"}
