{"id":"https://openalex.org/W2082244270","doi":"https://doi.org/10.1145/1516360.1516397","title":"Indexing density models for incremental learning and anytime classification on data streams","display_name":"Indexing density models for incremental learning and anytime classification on data streams","publication_year":2009,"publication_date":"2009-03-24","ids":{"openalex":"https://openalex.org/W2082244270","doi":"https://doi.org/10.1145/1516360.1516397","mag":"2082244270"},"language":"en","primary_location":{"id":"doi:10.1145/1516360.1516397","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1516360.1516397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology","raw_type":"proceedings-article"},"type":"article","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/A5003335849","display_name":"Thomas Seidl","orcid":"https://orcid.org/0000-0002-4861-1412"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Thomas Seidl","raw_affiliation_strings":["RWTH Aachen University, Germany"],"affiliations":[{"raw_affiliation_string":"RWTH Aachen University, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104360871","display_name":"Ira Assent","orcid":"https://orcid.org/0000-0002-1091-9948"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Ira Assent","raw_affiliation_strings":["Aalborg University, Denmark"],"affiliations":[{"raw_affiliation_string":"Aalborg University, Denmark","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113641260","display_name":"Philipp Kranen","orcid":null},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Philipp Kranen","raw_affiliation_strings":["RWTH Aachen University, Germany"],"affiliations":[{"raw_affiliation_string":"RWTH Aachen University, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049176185","display_name":"Ralph Krieger","orcid":null},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ralph Krieger","raw_affiliation_strings":["RWTH Aachen University, Germany"],"affiliations":[{"raw_affiliation_string":"RWTH Aachen University, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085526664","display_name":"Jennifer Herrmann","orcid":"https://orcid.org/0000-0003-3398-9938"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jennifer Herrmann","raw_affiliation_strings":["RWTH Aachen University, Germany"],"affiliations":[{"raw_affiliation_string":"RWTH Aachen University, Germany","institution_ids":["https://openalex.org/I887968799"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5003335849"],"corresponding_institution_ids":["https://openalex.org/I887968799"],"apc_list":null,"apc_paid":null,"fwci":7.6586,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.97243941,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"311","last_page":"322"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":1.0,"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":1.0,"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":0.9909999966621399,"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":0.9889000058174133,"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/computer-science","display_name":"Computer science","score":0.8105220794677734},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.6501291394233704},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.6273871064186096},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5957151055335999},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5766993761062622},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5665743350982666},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5511519312858582},{"id":"https://openalex.org/keywords/class-hierarchy","display_name":"Class hierarchy","score":0.5283991694450378},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.484968900680542},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4290539026260376},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.4226277470588684},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.4216015934944153},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41074174642562866},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.3972168564796448},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.2681318521499634},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11379292607307434},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10152631998062134},{"id":"https://openalex.org/keywords/object-oriented-programming","display_name":"Object-oriented programming","score":0.09705281257629395}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8105220794677734},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.6501291394233704},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.6273871064186096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5957151055335999},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5766993761062622},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5665743350982666},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5511519312858582},{"id":"https://openalex.org/C2781289151","wikidata":"https://www.wikidata.org/wiki/Q2903989","display_name":"Class hierarchy","level":3,"score":0.5283991694450378},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.484968900680542},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4290539026260376},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.4226277470588684},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.4216015934944153},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41074174642562866},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.3972168564796448},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2681318521499634},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11379292607307434},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10152631998062134},{"id":"https://openalex.org/C73752529","wikidata":"https://www.wikidata.org/wiki/Q79872","display_name":"Object-oriented programming","level":2,"score":0.09705281257629395},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/1516360.1516397","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1516360.1516397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.332.1579","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.332.1579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.edbt.org/Proceedings/2009-StPetersburg/edbt/papers/p0311-Seidl.pdf","raw_type":"text"},{"id":"pmh:oai:publications.rwth-aachen.de:125321","is_oa":false,"landing_page_url":"https://publications.rwth-aachen.de/record/125321","pdf_url":null,"source":{"id":"https://openalex.org/S4306401362","display_name":"RWTH Publications (RWTH Aachen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887968799","host_organization_name":"RWTH Aachen University","host_organization_lineage":["https://openalex.org/I887968799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Advances in Database Technology - EDBT 2009 : 12th International Conference on Extending Database Technology, Saint Petersburg, March 24 - 26, 2009 ; proceedings / eds: Martin Kersten ... Association for Computing Machinery<br/>12. International Conference on Extending Database Technology, EDBT 2009, Saint Petersburg, Russia, 2009-03-24 - 2009-03-26","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pure.atira.dk:publications/f07c52a0-fd3f-11de-9a61-000ea68e967b","is_oa":false,"landing_page_url":"https://vbn.aau.dk/da/publications/f07c52a0-fd3f-11de-9a61-000ea68e967b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Seidl , T , Assent , I , Kranen , P , Krieger , R &amp; Herrmann , J 2009 , Indexing Density Models for Incremental Learning and Anytime Classification on Data Streams . in Extending Database Technology (EDBT 2009), Saint-Petersburg, Russia : Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology . vol. 360 , Association for Computing Machinery , ACM International Conference Proceeding Series (ICPS) , no. 360 , pp. 311-322 , International Conference on Extending Database Technology (EDBT 2009) , Saint-Petersburg , Russian Federation , 24/03/2009 . https://doi.org/10.1145/1516360.1516397","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W277006528","https://openalex.org/W1480376833","https://openalex.org/W1484610779","https://openalex.org/W1490760466","https://openalex.org/W1504694836","https://openalex.org/W1516914187","https://openalex.org/W1538023239","https://openalex.org/W1561056154","https://openalex.org/W1878118044","https://openalex.org/W1972676371","https://openalex.org/W1981038597","https://openalex.org/W1990079212","https://openalex.org/W2009727399","https://openalex.org/W2011823784","https://openalex.org/W2022775778","https://openalex.org/W2025653905","https://openalex.org/W2026237073","https://openalex.org/W2034870679","https://openalex.org/W2068714596","https://openalex.org/W2075542647","https://openalex.org/W2089624555","https://openalex.org/W2100188668","https://openalex.org/W2118262610","https://openalex.org/W2118269922","https://openalex.org/W2118462151","https://openalex.org/W2121423746","https://openalex.org/W2125055259","https://openalex.org/W2129905273","https://openalex.org/W2134627110","https://openalex.org/W2139212933","https://openalex.org/W2148928503","https://openalex.org/W2151135734","https://openalex.org/W2152497905","https://openalex.org/W2163316275","https://openalex.org/W2411921399","https://openalex.org/W3083113686","https://openalex.org/W3193477162","https://openalex.org/W4244494905","https://openalex.org/W4246744641","https://openalex.org/W6628633436","https://openalex.org/W6629109325","https://openalex.org/W6629451354","https://openalex.org/W6633640926","https://openalex.org/W6675485694","https://openalex.org/W6677768686","https://openalex.org/W6715097780"],"related_works":["https://openalex.org/W4389449520","https://openalex.org/W127192698","https://openalex.org/W2570600173","https://openalex.org/W2893008024","https://openalex.org/W2743735673","https://openalex.org/W2360131081","https://openalex.org/W2985941356","https://openalex.org/W4361801939","https://openalex.org/W2802243998","https://openalex.org/W1521014365"],"abstract_inverted_index":{"Classification":[0],"of":[1,15,65,96,129,150],"streaming":[2],"data":[3,23,35,49],"faces":[4],"three":[5,64],"basic":[6],"challenges:":[7],"it":[8],"has":[9],"to":[10,47,87,91],"deal":[11],"with":[12,113],"huge":[13],"amounts":[14],"data,":[16],"the":[17,44,66,70,88,119,146,151],"varying":[18],"time":[19],"between":[20],"two":[21],"stream":[22],"items":[24],"must":[25,36],"be":[26,37,92],"used":[27],"best":[28],"possible":[29],"(anytime":[30,40],"classification)":[31],"and":[32,144],"additional":[33],"training":[34],"incrementally":[38],"learned":[39],"learning)":[41],"for":[42,122,138],"applying":[43],"classifier":[45,73],"consistently":[46],"fast":[48],"streams.":[50],"In":[51],"this":[52],"work,":[53],"we":[54,132],"propose":[55,133],"a":[56,94,134],"novel":[57,80,114,135],"index-based":[58],"technique":[59],"that":[60,99],"can":[61],"handle":[62],"all":[63],"above":[67],"challenges":[68],"using":[69,141],"established":[71],"Bayes":[72,81,152],"on":[74],"effective":[75,124],"kernel":[76,101],"density":[77,102,110],"estimators.":[78],"Our":[79,108],"tree":[82],"automatically":[83],"generates":[84],"(adapted":[85],"efficiently":[86],"individual":[89],"object":[90],"classified)":[93],"hierarchy":[95],"mixture":[97],"densities":[98],"represent":[100],"estimators":[103],"at":[104,126],"successively":[105],"coarser":[106],"levels.":[107],"probability":[109],"queries":[111],"together":[112],"classification":[115,125,140],"improvement":[116],"strategies":[117],"provide":[118],"necessary":[120],"information":[121],"very":[123],"any":[127],"point":[128],"interruption.":[130],"Moreover,":[131],"evaluation":[136],"method":[137],"anytime":[139,147],"Poisson":[142],"streams":[143],"demonstrate":[145],"learning":[148],"performance":[149],"tree.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":3},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":5},{"year":2012,"cited_by_count":5}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
