{"id":"https://openalex.org/W2291006719","doi":"https://doi.org/10.1186/s40537-016-0040-9","title":"Role of big-data in classification and novel class detection in data streams","display_name":"Role of big-data in classification and novel class detection in data streams","publication_year":2016,"publication_date":"2016-03-04","ids":{"openalex":"https://openalex.org/W2291006719","doi":"https://doi.org/10.1186/s40537-016-0040-9","mag":"2291006719"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-016-0040-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-016-0040-9","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-016-0040-9","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"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":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-016-0040-9","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005115148","display_name":"Manoj B. Chandak","orcid":"https://orcid.org/0000-0002-0103-4224"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"M. B. Chandak","raw_affiliation_strings":["Department of Computer Science & Engineering, Ramdeobaba College of Engineering and Management, Nagpur, India"],"raw_orcid":"https://orcid.org/0000-0002-0103-4224","affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, Ramdeobaba College of Engineering and Management, Nagpur, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5005115148"],"corresponding_institution_ids":[],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":7.0675,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.96924207,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"3","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9998999834060669,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9970999956130981,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9944999814033508,"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/data-stream-mining","display_name":"Data stream mining","score":0.8910555243492126},{"id":"https://openalex.org/keywords/concept-drift","display_name":"Concept drift","score":0.8400478363037109},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8254867196083069},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6276100277900696},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.6213165521621704},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.596378743648529},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5445064306259155},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5270419716835022},{"id":"https://openalex.org/keywords/streams","display_name":"STREAMS","score":0.5125288963317871},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47701144218444824},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3613477945327759},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3219457268714905}],"concepts":[{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.8910555243492126},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.8400478363037109},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8254867196083069},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6276100277900696},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.6213165521621704},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.596378743648529},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5445064306259155},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5270419716835022},{"id":"https://openalex.org/C42090638","wikidata":"https://www.wikidata.org/wiki/Q4048907","display_name":"STREAMS","level":2,"score":0.5125288963317871},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47701144218444824},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3613477945327759},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3219457268714905},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1186/s40537-016-0040-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-016-0040-9","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-016-0040-9","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"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":"Journal of Big Data","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1186/s40537-016-0040-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-016-0040-9","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-016-0040-9","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"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":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2291006719.pdf","grobid_xml":"https://content.openalex.org/works/W2291006719.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W1521014365","https://openalex.org/W1998960312","https://openalex.org/W2030680965","https://openalex.org/W2095953800","https://openalex.org/W2116413397","https://openalex.org/W2124077530","https://openalex.org/W2128750409","https://openalex.org/W2130416896","https://openalex.org/W2142772712","https://openalex.org/W2161835057","https://openalex.org/W2168386304"],"related_works":["https://openalex.org/W4307392573","https://openalex.org/W2802243998","https://openalex.org/W2736127210","https://openalex.org/W2329342202","https://openalex.org/W2574092225","https://openalex.org/W4200217704","https://openalex.org/W2161835057","https://openalex.org/W1521014365","https://openalex.org/W2740428142","https://openalex.org/W2187127952"],"abstract_inverted_index":{"\u201cData":[0],"streams\u201d":[1,161],"is":[2,36,70,80,101,123,137],"defined":[3],"as":[4],"class":[5],"of":[6,21,27,51,74,88,95,109,134,141,166],"data":[7,42,52,75,116],"generated":[8],"over":[9],"\u201ctext,":[10],"audio":[11],"and":[12,24,40,46,66,107,143,162,169],"video\u201d":[13],"channel":[14],"in":[15,85,98,127,149],"continuous":[16],"form.":[17],"The":[18,49,125,145],"streams":[19,43],"are":[20,61],"infinite":[22,62],"length":[23],"may":[25],"comprise":[26],"structured":[28],"or":[29],"unstructured":[30],"data.":[31,99],"With":[32],"these":[33],"features,":[34],"it":[35],"difficult":[37],"to":[38,58,82,93,103,120,158],"store":[39],"process":[41,159],"with":[44],"simple":[45],"static":[47],"strategies.":[48],"processing":[50],"stream":[53],"poses":[54],"four":[55],"main":[56],"challenges":[57,165],"researchers.":[59],"These":[60],"length,":[63],"concept-evolution,":[64],"concept-drift":[65],"feature":[67],"evolution.":[68],"Infinite-length":[69],"because":[71],"the":[72,86,118,135,150,164],"amount":[73],"has":[76],"no":[77],"bounds.":[78],"Concept-drift":[79],"due":[81,92,102],"slow":[83],"changes":[84],"concept":[87],"stream.":[89],"Concept-evolution":[90],"occurs":[91],"presence":[94],"unknown":[96],"classes":[97],"Feature-evolution":[100],"progression":[104],"new":[105],"features":[106],"regression":[108],"old":[110],"features.":[111],"To":[112],"perform":[113],"any":[114],"analytics":[115],"streams,":[117],"conversion":[119],"knowledgable":[121],"form":[122],"essential.":[124],"researcher":[126],"past":[128],"have":[129],"proposed":[130],"various":[131],"strategies,":[132],"most":[133],"research":[136,146],"focussed":[138],"on":[139],"problem":[140],"infinite-length":[142],"concept-drift.":[144,170],"work":[147],"presented":[148],"paper":[151],"describes":[152],"a":[153],"efficient":[154],"string":[155],"based":[156],"methodology":[157],"\u201cdata":[160],"control":[163],"infinite-length,":[167],"concept-evolution":[168],"Subject":[171],"areas":[172],"Data":[173],"mining,":[174],"Machine":[175],"learning":[176]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
