{"id":"https://openalex.org/W2071679154","doi":"https://doi.org/10.1145/1458082.1458164","title":"A framework for estimating complex probability density structures in data streams","display_name":"A framework for estimating complex probability density structures in data streams","publication_year":2008,"publication_date":"2008-10-26","ids":{"openalex":"https://openalex.org/W2071679154","doi":"https://doi.org/10.1145/1458082.1458164","mag":"2071679154"},"language":"en","primary_location":{"id":"doi:10.1145/1458082.1458164","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1458082.1458164","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM conference on Information and knowledge management","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/A5033884416","display_name":"Arnold P. Boedihardjo","orcid":null},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Arnold P. Boedihardjo","raw_affiliation_strings":["Virginia Tech, Falls Church, VA, USA","Virginia Tech., Falls Church, VA, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Tech, Falls Church, VA, USA","institution_ids":["https://openalex.org/I859038795"]},{"raw_affiliation_string":"Virginia Tech., Falls Church, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038002204","display_name":"Chang\u2010Tien Lu","orcid":"https://orcid.org/0000-0003-3675-0199"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chang-Tien Lu","raw_affiliation_strings":["Virginia Tech, Falls Church, VA, USA","Virginia Tech., Falls Church, VA, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Tech, Falls Church, VA, USA","institution_ids":["https://openalex.org/I859038795"]},{"raw_affiliation_string":"Virginia Tech., Falls Church, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100352703","display_name":"Feng Chen","orcid":"https://orcid.org/0000-0002-4508-5963"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feng Chen","raw_affiliation_strings":["Virginia Tech, Falls Church, VA, USA","Virginia Tech., Falls Church, VA, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Tech, Falls Church, VA, USA","institution_ids":["https://openalex.org/I859038795"]},{"raw_affiliation_string":"Virginia Tech., Falls Church, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5033884416"],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":null,"apc_paid":null,"fwci":1.1198,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.77986167,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"619","last_page":"628"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9994000196456909,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9991000294685364,"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":0.9990000128746033,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6990439891815186},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.568798303604126},{"id":"https://openalex.org/keywords/streams","display_name":"STREAMS","score":0.5397163033485413},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.5345035791397095},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41521143913269043},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23314577341079712},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1305665373802185},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.07489079236984253}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6990439891815186},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.568798303604126},{"id":"https://openalex.org/C42090638","wikidata":"https://www.wikidata.org/wiki/Q4048907","display_name":"STREAMS","level":2,"score":0.5397163033485413},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.5345035791397095},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41521143913269043},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23314577341079712},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1305665373802185},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.07489079236984253}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1458082.1458164","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1458082.1458164","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM conference on Information and knowledge management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W70607902","https://openalex.org/W115840729","https://openalex.org/W204885769","https://openalex.org/W1766932551","https://openalex.org/W1949687736","https://openalex.org/W1981038597","https://openalex.org/W1981161816","https://openalex.org/W1992023276","https://openalex.org/W2001474264","https://openalex.org/W2002847183","https://openalex.org/W2031613530","https://openalex.org/W2039260438","https://openalex.org/W2057058417","https://openalex.org/W2082553115","https://openalex.org/W2095668224","https://openalex.org/W2095897464","https://openalex.org/W2098494487","https://openalex.org/W2118020555","https://openalex.org/W2129905273","https://openalex.org/W2151310484","https://openalex.org/W2153610999","https://openalex.org/W2394914089","https://openalex.org/W2615478764","https://openalex.org/W2990650678","https://openalex.org/W3120740533","https://openalex.org/W6602894946","https://openalex.org/W6604618597","https://openalex.org/W6671428793","https://openalex.org/W6682418189","https://openalex.org/W6711887999"],"related_works":["https://openalex.org/W2313030483","https://openalex.org/W1582424504","https://openalex.org/W2067164079","https://openalex.org/W2378640446","https://openalex.org/W1518573110","https://openalex.org/W2334651808","https://openalex.org/W2366772082","https://openalex.org/W2039848804","https://openalex.org/W2358793424","https://openalex.org/W205648239"],"abstract_inverted_index":{"Probability":[0],"density":[1,23,89],"function":[2],"estimation":[3],"is":[4],"a":[5,27,92,101],"fundamental":[6],"component":[7],"in":[8],"several":[9],"stream":[10,51,76],"mining":[11],"tasks":[12],"such":[13],"as":[14],"outlier":[15],"detection":[16],"and":[17,29,61,105,111,122,130],"classification.":[18],"The":[19],"nonparametric":[20],"adaptive":[21],"kernel":[22],"estimate":[24,32],"(AKDE)":[25],"provides":[26],"robust":[28],"asymptotically":[30,62],"consistent":[31,63],"for":[33],"an":[34],"arbitrary":[35],"distribution.":[36],"However,":[37],"its":[38],"extensive":[39,116],"computational":[40,112],"requirements":[41],"make":[42],"it":[43],"difficult":[44],"to":[45,49,85,96,126],"apply":[46],"this":[47],"technique":[48],"the":[50,56,70,75,80,98,107,128],"environment.":[52,77],"This":[53],"paper":[54],"tackles":[55],"issue":[57],"of":[58,82,94,132],"developing":[59],"efficient":[60],"AKDE":[64,99],"over":[65],"data":[66,124],"streams":[67],"while":[68],"heeding":[69],"stringent":[71],"constraints":[72],"imposed":[73],"by":[74],"We":[78],"propose":[79],"concept":[81],"local":[83,88],"regions":[84],"effectively":[86],"synopsize":[87],"features,":[90],"design":[91],"suite":[93],"algorithms":[95],"maintain":[97],"under":[100],"time-based":[102],"sliding":[103],"window,":[104],"analyze":[106],"estimates'":[108],"asymptotic":[109],"consistency":[110],"costs.":[113],"In":[114],"addition,":[115],"experiments":[117],"were":[118],"conducted":[119],"with":[120],"real-world":[121],"synthetic":[123],"sets":[125],"demonstrate":[127],"effectiveness":[129],"efficiency":[131],"our":[133],"approach.":[134]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}